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#define __Pyx_PyString_FormatSafe(a, b)   ((unlikely((a) == Py_None)) ? PyNumber_Remainder(a, b) : __Pyx_PyString_Format(a, b))
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#if PY_MAJOR_VERSION >= 3
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#if PY_MAJOR_VERSION >= 3
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#define __Pyx_TypeCheck(obj, type) PyObject_TypeCheck(obj, (PyTypeObject *)type)
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  #define PyInt_FromSsize_t            PyLong_FromSsize_t
  #define PyInt_AsLong                 PyLong_AsLong
  #define PyInt_AS_LONG                PyLong_AS_LONG
  #define PyInt_AsSsize_t              PyLong_AsSsize_t
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  #define PyInt_AsUnsignedLongLongMask PyLong_AsUnsignedLongLongMask
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#if PY_MAJOR_VERSION >= 3
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#if PY_MAJOR_VERSION >= 3 && CYTHON_COMPILING_IN_PYPY
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    #define CYTHON_INLINE inline
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    #define CYTHON_INLINE
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#ifndef CYTHON_RESTRICT
  #if defined(__GNUC__)
    #define CYTHON_RESTRICT __restrict__
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#ifdef NAN
#define __PYX_NAN() ((float) NAN)
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static CYTHON_INLINE float __PYX_NAN() {
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}
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#define __Pyx_void_to_None(void_result) (void_result, Py_INCREF(Py_None), Py_None)
#ifdef __cplusplus
template<typename T>
void __Pyx_call_destructor(T* x) {
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template<typename T>
class __Pyx_FakeReference {
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  private:
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#if PY_MAJOR_VERSION >= 3
  #define __Pyx_PyNumber_Divide(x,y)         PyNumber_TrueDivide(x,y)
  #define __Pyx_PyNumber_InPlaceDivide(x,y)  PyNumber_InPlaceTrueDivide(x,y)
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  #define __Pyx_PyNumber_Divide(x,y)         PyNumber_Divide(x,y)
  #define __Pyx_PyNumber_InPlaceDivide(x,y)  PyNumber_InPlaceDivide(x,y)
#endif

#ifndef __PYX_EXTERN_C
  #ifdef __cplusplus
    #define __PYX_EXTERN_C extern "C"
  #else
    #define __PYX_EXTERN_C extern
  #endif
#endif

#if defined(WIN32) || defined(MS_WINDOWS)
#define _USE_MATH_DEFINES
#endif
#include <math.h>
#define __PYX_HAVE__statsmodels__tsa__statespace___statespace
#define __PYX_HAVE_API__statsmodels__tsa__statespace___statespace
#include "string.h"
#include "stdio.h"
#include "stdlib.h"
#include "numpy/arrayobject.h"
#include "numpy/ufuncobject.h"
#include "math.h"
#include "numpy/npy_math.h"
#include "capsule.h"
#include "pythread.h"
#include "pystate.h"
#ifdef _OPENMP
#include <omp.h>
#endif /* _OPENMP */

#ifdef PYREX_WITHOUT_ASSERTIONS
#define CYTHON_WITHOUT_ASSERTIONS
#endif

#ifndef CYTHON_UNUSED
# if defined(__GNUC__)
#   if !(defined(__cplusplus)) || (__GNUC__ > 3 || (__GNUC__ == 3 && __GNUC_MINOR__ >= 4))
#     define CYTHON_UNUSED __attribute__ ((__unused__))
#   else
#     define CYTHON_UNUSED
#   endif
# elif defined(__ICC) || (defined(__INTEL_COMPILER) && !defined(_MSC_VER))
#   define CYTHON_UNUSED __attribute__ ((__unused__))
# else
#   define CYTHON_UNUSED
# endif
#endif
typedef struct {PyObject **p; char *s; const Py_ssize_t n; const char* encoding;
                const char is_unicode; const char is_str; const char intern; } __Pyx_StringTabEntry;

#define __PYX_DEFAULT_STRING_ENCODING_IS_ASCII 0
#define __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT 0
#define __PYX_DEFAULT_STRING_ENCODING ""
#define __Pyx_PyObject_FromString __Pyx_PyBytes_FromString
#define __Pyx_PyObject_FromStringAndSize __Pyx_PyBytes_FromStringAndSize
#define __Pyx_fits_Py_ssize_t(v, type, is_signed)  (    \
    (sizeof(type) < sizeof(Py_ssize_t))  ||             \
    (sizeof(type) > sizeof(Py_ssize_t) &&               \
          likely(v < (type)PY_SSIZE_T_MAX ||            \
                 v == (type)PY_SSIZE_T_MAX)  &&         \
          (!is_signed || likely(v > (type)PY_SSIZE_T_MIN ||       \
                                v == (type)PY_SSIZE_T_MIN)))  ||  \
    (sizeof(type) == sizeof(Py_ssize_t) &&              \
          (is_signed || likely(v < (type)PY_SSIZE_T_MAX ||        \
                               v == (type)PY_SSIZE_T_MAX)))  )
static CYTHON_INLINE char* __Pyx_PyObject_AsString(PyObject*);
static CYTHON_INLINE char* __Pyx_PyObject_AsStringAndSize(PyObject*, Py_ssize_t* length);
#define __Pyx_PyByteArray_FromString(s) PyByteArray_FromStringAndSize((const char*)s, strlen((const char*)s))
#define __Pyx_PyByteArray_FromStringAndSize(s, l) PyByteArray_FromStringAndSize((const char*)s, l)
#define __Pyx_PyBytes_FromString        PyBytes_FromString
#define __Pyx_PyBytes_FromStringAndSize PyBytes_FromStringAndSize
static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char*);
#if PY_MAJOR_VERSION < 3
    #define __Pyx_PyStr_FromString        __Pyx_PyBytes_FromString
    #define __Pyx_PyStr_FromStringAndSize __Pyx_PyBytes_FromStringAndSize
#else
    #define __Pyx_PyStr_FromString        __Pyx_PyUnicode_FromString
    #define __Pyx_PyStr_FromStringAndSize __Pyx_PyUnicode_FromStringAndSize
#endif
#define __Pyx_PyObject_AsSString(s)    ((signed char*) __Pyx_PyObject_AsString(s))
#define __Pyx_PyObject_AsUString(s)    ((unsigned char*) __Pyx_PyObject_AsString(s))
#define __Pyx_PyObject_FromCString(s)  __Pyx_PyObject_FromString((const char*)s)
#define __Pyx_PyBytes_FromCString(s)   __Pyx_PyBytes_FromString((const char*)s)
#define __Pyx_PyByteArray_FromCString(s)   __Pyx_PyByteArray_FromString((const char*)s)
#define __Pyx_PyStr_FromCString(s)     __Pyx_PyStr_FromString((const char*)s)
#define __Pyx_PyUnicode_FromCString(s) __Pyx_PyUnicode_FromString((const char*)s)
#if PY_MAJOR_VERSION < 3
static CYTHON_INLINE size_t __Pyx_Py_UNICODE_strlen(const Py_UNICODE *u)
{
    const Py_UNICODE *u_end = u;
    while (*u_end++) ;
    return (size_t)(u_end - u - 1);
}
#else
#define __Pyx_Py_UNICODE_strlen Py_UNICODE_strlen
#endif
#define __Pyx_PyUnicode_FromUnicode(u)       PyUnicode_FromUnicode(u, __Pyx_Py_UNICODE_strlen(u))
#define __Pyx_PyUnicode_FromUnicodeAndLength PyUnicode_FromUnicode
#define __Pyx_PyUnicode_AsUnicode            PyUnicode_AsUnicode
#define __Pyx_Owned_Py_None(b) (Py_INCREF(Py_None), Py_None)
#define __Pyx_PyBool_FromLong(b) ((b) ? (Py_INCREF(Py_True), Py_True) : (Py_INCREF(Py_False), Py_False))
static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject*);
static CYTHON_INLINE PyObject* __Pyx_PyNumber_Int(PyObject* x);
static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject*);
static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t);
#if CYTHON_COMPILING_IN_CPYTHON
#define __pyx_PyFloat_AsDouble(x) (PyFloat_CheckExact(x) ? PyFloat_AS_DOUBLE(x) : PyFloat_AsDouble(x))
#else
#define __pyx_PyFloat_AsDouble(x) PyFloat_AsDouble(x)
#endif
#define __pyx_PyFloat_AsFloat(x) ((float) __pyx_PyFloat_AsDouble(x))
#if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII
static int __Pyx_sys_getdefaultencoding_not_ascii;
static int __Pyx_init_sys_getdefaultencoding_params(void) {
    PyObject* sys;
    PyObject* default_encoding = NULL;
    PyObject* ascii_chars_u = NULL;
    PyObject* ascii_chars_b = NULL;
    const char* default_encoding_c;
    sys = PyImport_ImportModule("sys");
    if (!sys) goto bad;
    default_encoding = PyObject_CallMethod(sys, (char*) "getdefaultencoding", NULL);
    Py_DECREF(sys);
    if (!default_encoding) goto bad;
    default_encoding_c = PyBytes_AsString(default_encoding);
    if (!default_encoding_c) goto bad;
    if (strcmp(default_encoding_c, "ascii") == 0) {
        __Pyx_sys_getdefaultencoding_not_ascii = 0;
    } else {
        char ascii_chars[128];
        int c;
        for (c = 0; c < 128; c++) {
            ascii_chars[c] = c;
        }
        __Pyx_sys_getdefaultencoding_not_ascii = 1;
        ascii_chars_u = PyUnicode_DecodeASCII(ascii_chars, 128, NULL);
        if (!ascii_chars_u) goto bad;
        ascii_chars_b = PyUnicode_AsEncodedString(ascii_chars_u, default_encoding_c, NULL);
        if (!ascii_chars_b || !PyBytes_Check(ascii_chars_b) || memcmp(ascii_chars, PyBytes_AS_STRING(ascii_chars_b), 128) != 0) {
            PyErr_Format(
                PyExc_ValueError,
                "This module compiled with c_string_encoding=ascii, but default encoding '%.200s' is not a superset of ascii.",
                default_encoding_c);
            goto bad;
        }
        Py_DECREF(ascii_chars_u);
        Py_DECREF(ascii_chars_b);
    }
    Py_DECREF(default_encoding);
    return 0;
bad:
    Py_XDECREF(default_encoding);
    Py_XDECREF(ascii_chars_u);
    Py_XDECREF(ascii_chars_b);
    return -1;
}
#endif
#if __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT && PY_MAJOR_VERSION >= 3
#define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_DecodeUTF8(c_str, size, NULL)
#else
#define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_Decode(c_str, size, __PYX_DEFAULT_STRING_ENCODING, NULL)
#if __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT
static char* __PYX_DEFAULT_STRING_ENCODING;
static int __Pyx_init_sys_getdefaultencoding_params(void) {
    PyObject* sys;
    PyObject* default_encoding = NULL;
    char* default_encoding_c;
    sys = PyImport_ImportModule("sys");
    if (!sys) goto bad;
    default_encoding = PyObject_CallMethod(sys, (char*) (const char*) "getdefaultencoding", NULL);
    Py_DECREF(sys);
    if (!default_encoding) goto bad;
    default_encoding_c = PyBytes_AsString(default_encoding);
    if (!default_encoding_c) goto bad;
    __PYX_DEFAULT_STRING_ENCODING = (char*) malloc(strlen(default_encoding_c));
    if (!__PYX_DEFAULT_STRING_ENCODING) goto bad;
    strcpy(__PYX_DEFAULT_STRING_ENCODING, default_encoding_c);
    Py_DECREF(default_encoding);
    return 0;
bad:
    Py_XDECREF(default_encoding);
    return -1;
}
#endif
#endif


/* Test for GCC > 2.95 */
#if defined(__GNUC__)     && (__GNUC__ > 2 || (__GNUC__ == 2 && (__GNUC_MINOR__ > 95)))
  #define likely(x)   __builtin_expect(!!(x), 1)
  #define unlikely(x) __builtin_expect(!!(x), 0)
#else /* !__GNUC__ or GCC < 2.95 */
  #define likely(x)   (x)
  #define unlikely(x) (x)
#endif /* __GNUC__ */

static PyObject *__pyx_m;
static PyObject *__pyx_d;
static PyObject *__pyx_b;
static PyObject *__pyx_empty_tuple;
static PyObject *__pyx_empty_bytes;
static int __pyx_lineno;
static int __pyx_clineno = 0;
static const char * __pyx_cfilenm= __FILE__;
static const char *__pyx_filename;

#if !defined(CYTHON_CCOMPLEX)
  #if defined(__cplusplus)
    #define CYTHON_CCOMPLEX 1
  #elif defined(_Complex_I)
    #define CYTHON_CCOMPLEX 1
  #else
    #define CYTHON_CCOMPLEX 0
  #endif
#endif
#if CYTHON_CCOMPLEX
  #ifdef __cplusplus
    #include <complex>
  #else
    #include <complex.h>
  #endif
#endif
#if CYTHON_CCOMPLEX && !defined(__cplusplus) && defined(__sun__) && defined(__GNUC__)
  #undef _Complex_I
  #define _Complex_I 1.0fj
#endif


static const char *__pyx_f[] = {
  "statsmodels\\tsa\\statespace\\_statespace.pyx",
  "__init__.pxd",
  "statsmodels\\tsa\\statespace\\stringsource",
  "type.pxd",
};
struct __pyx_memoryview_obj;
typedef struct {
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  char *data;
  Py_ssize_t shape[8];
  Py_ssize_t strides[8];
  Py_ssize_t suboffsets[8];
} __Pyx_memviewslice;

#define IS_UNSIGNED(type) (((type) -1) > 0)
struct __Pyx_StructField_;
#define __PYX_BUF_FLAGS_PACKED_STRUCT (1 << 0)
typedef struct {
  const char* name;
  struct __Pyx_StructField_* fields;
  size_t size;
  size_t arraysize[8];
  int ndim;
  char typegroup;
  char is_unsigned;
  int flags;
} __Pyx_TypeInfo;
typedef struct __Pyx_StructField_ {
  __Pyx_TypeInfo* type;
  const char* name;
  size_t offset;
} __Pyx_StructField;
typedef struct {
  __Pyx_StructField* field;
  size_t parent_offset;
} __Pyx_BufFmt_StackElem;
typedef struct {
  __Pyx_StructField root;
  __Pyx_BufFmt_StackElem* head;
  size_t fmt_offset;
  size_t new_count, enc_count;
  size_t struct_alignment;
  int is_complex;
  char enc_type;
  char new_packmode;
  char enc_packmode;
  char is_valid_array;
} __Pyx_BufFmt_Context;

#include <pythread.h>
#ifndef CYTHON_ATOMICS
    #define CYTHON_ATOMICS 1
#endif
#define __pyx_atomic_int_type int
#if CYTHON_ATOMICS && __GNUC__ >= 4 && (__GNUC_MINOR__ > 1 ||           \
                    (__GNUC_MINOR__ == 1 && __GNUC_PATCHLEVEL >= 2)) && \
                    !defined(__i386__)
    #define __pyx_atomic_incr_aligned(value, lock) __sync_fetch_and_add(value, 1)
    #define __pyx_atomic_decr_aligned(value, lock) __sync_fetch_and_sub(value, 1)
    #ifdef __PYX_DEBUG_ATOMICS
        #warning "Using GNU atomics"
    #endif
#elif CYTHON_ATOMICS && MSC_VER
    #include <Windows.h>
    #define __pyx_atomic_int_type LONG
    #define __pyx_atomic_incr_aligned(value, lock) InterlockedIncrement(value)
    #define __pyx_atomic_decr_aligned(value, lock) InterlockedDecrement(value)
    #ifdef __PYX_DEBUG_ATOMICS
        #warning "Using MSVC atomics"
    #endif
#elif CYTHON_ATOMICS && (defined(__ICC) || defined(__INTEL_COMPILER)) && 0
    #define __pyx_atomic_incr_aligned(value, lock) _InterlockedIncrement(value)
    #define __pyx_atomic_decr_aligned(value, lock) _InterlockedDecrement(value)
    #ifdef __PYX_DEBUG_ATOMICS
        #warning "Using Intel atomics"
    #endif
#else
    #undef CYTHON_ATOMICS
    #define CYTHON_ATOMICS 0
    #ifdef __PYX_DEBUG_ATOMICS
        #warning "Not using atomics"
    #endif
#endif
typedef volatile __pyx_atomic_int_type __pyx_atomic_int;
#if CYTHON_ATOMICS
    #define __pyx_add_acquisition_count(memview) \
             __pyx_atomic_incr_aligned(__pyx_get_slice_count_pointer(memview), memview->lock)
    #define __pyx_sub_acquisition_count(memview) \
            __pyx_atomic_decr_aligned(__pyx_get_slice_count_pointer(memview), memview->lock)
#else
    #define __pyx_add_acquisition_count(memview) \
            __pyx_add_acquisition_count_locked(__pyx_get_slice_count_pointer(memview), memview->lock)
    #define __pyx_sub_acquisition_count(memview) \
            __pyx_sub_acquisition_count_locked(__pyx_get_slice_count_pointer(memview), memview->lock)
#endif


/* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":726
 * # in Cython to enable them only on the right systems.
 * 
 * ctypedef npy_int8       int8_t             # <<<<<<<<<<<<<<
 * ctypedef npy_int16      int16_t
 * ctypedef npy_int32      int32_t
 */
typedef npy_int8 __pyx_t_5numpy_int8_t;

/* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":727
 * 
 * ctypedef npy_int8       int8_t
 * ctypedef npy_int16      int16_t             # <<<<<<<<<<<<<<
 * ctypedef npy_int32      int32_t
 * ctypedef npy_int64      int64_t
 */
typedef npy_int16 __pyx_t_5numpy_int16_t;

/* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":728
 * ctypedef npy_int8       int8_t
 * ctypedef npy_int16      int16_t
 * ctypedef npy_int32      int32_t             # <<<<<<<<<<<<<<
 * ctypedef npy_int64      int64_t
 * #ctypedef npy_int96      int96_t
 */
typedef npy_int32 __pyx_t_5numpy_int32_t;

/* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":729
 * ctypedef npy_int16      int16_t
 * ctypedef npy_int32      int32_t
 * ctypedef npy_int64      int64_t             # <<<<<<<<<<<<<<
 * #ctypedef npy_int96      int96_t
 * #ctypedef npy_int128     int128_t
 */
typedef npy_int64 __pyx_t_5numpy_int64_t;

/* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":733
 * #ctypedef npy_int128     int128_t
 * 
 * ctypedef npy_uint8      uint8_t             # <<<<<<<<<<<<<<
 * ctypedef npy_uint16     uint16_t
 * ctypedef npy_uint32     uint32_t
 */
typedef npy_uint8 __pyx_t_5numpy_uint8_t;

/* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":734
 * 
 * ctypedef npy_uint8      uint8_t
 * ctypedef npy_uint16     uint16_t             # <<<<<<<<<<<<<<
 * ctypedef npy_uint32     uint32_t
 * ctypedef npy_uint64     uint64_t
 */
typedef npy_uint16 __pyx_t_5numpy_uint16_t;

/* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":735
 * ctypedef npy_uint8      uint8_t
 * ctypedef npy_uint16     uint16_t
 * ctypedef npy_uint32     uint32_t             # <<<<<<<<<<<<<<
 * ctypedef npy_uint64     uint64_t
 * #ctypedef npy_uint96     uint96_t
 */
typedef npy_uint32 __pyx_t_5numpy_uint32_t;

/* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":736
 * ctypedef npy_uint16     uint16_t
 * ctypedef npy_uint32     uint32_t
 * ctypedef npy_uint64     uint64_t             # <<<<<<<<<<<<<<
 * #ctypedef npy_uint96     uint96_t
 * #ctypedef npy_uint128    uint128_t
 */
typedef npy_uint64 __pyx_t_5numpy_uint64_t;

/* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":740
 * #ctypedef npy_uint128    uint128_t
 * 
 * ctypedef npy_float32    float32_t             # <<<<<<<<<<<<<<
 * ctypedef npy_float64    float64_t
 * #ctypedef npy_float80    float80_t
 */
typedef npy_float32 __pyx_t_5numpy_float32_t;

/* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":741
 * 
 * ctypedef npy_float32    float32_t
 * ctypedef npy_float64    float64_t             # <<<<<<<<<<<<<<
 * #ctypedef npy_float80    float80_t
 * #ctypedef npy_float128   float128_t
 */
typedef npy_float64 __pyx_t_5numpy_float64_t;

/* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":750
 * # The int types are mapped a bit surprising --
 * # numpy.int corresponds to 'l' and numpy.long to 'q'
 * ctypedef npy_long       int_t             # <<<<<<<<<<<<<<
 * ctypedef npy_longlong   long_t
 * ctypedef npy_longlong   longlong_t
 */
typedef npy_long __pyx_t_5numpy_int_t;

/* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":751
 * # numpy.int corresponds to 'l' and numpy.long to 'q'
 * ctypedef npy_long       int_t
 * ctypedef npy_longlong   long_t             # <<<<<<<<<<<<<<
 * ctypedef npy_longlong   longlong_t
 * 
 */
typedef npy_longlong __pyx_t_5numpy_long_t;

/* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":752
 * ctypedef npy_long       int_t
 * ctypedef npy_longlong   long_t
 * ctypedef npy_longlong   longlong_t             # <<<<<<<<<<<<<<
 * 
 * ctypedef npy_ulong      uint_t
 */
typedef npy_longlong __pyx_t_5numpy_longlong_t;

/* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":754
 * ctypedef npy_longlong   longlong_t
 * 
 * ctypedef npy_ulong      uint_t             # <<<<<<<<<<<<<<
 * ctypedef npy_ulonglong  ulong_t
 * ctypedef npy_ulonglong  ulonglong_t
 */
typedef npy_ulong __pyx_t_5numpy_uint_t;

/* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":755
 * 
 * ctypedef npy_ulong      uint_t
 * ctypedef npy_ulonglong  ulong_t             # <<<<<<<<<<<<<<
 * ctypedef npy_ulonglong  ulonglong_t
 * 
 */
typedef npy_ulonglong __pyx_t_5numpy_ulong_t;

/* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":756
 * ctypedef npy_ulong      uint_t
 * ctypedef npy_ulonglong  ulong_t
 * ctypedef npy_ulonglong  ulonglong_t             # <<<<<<<<<<<<<<
 * 
 * ctypedef npy_intp       intp_t
 */
typedef npy_ulonglong __pyx_t_5numpy_ulonglong_t;

/* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":758
 * ctypedef npy_ulonglong  ulonglong_t
 * 
 * ctypedef npy_intp       intp_t             # <<<<<<<<<<<<<<
 * ctypedef npy_uintp      uintp_t
 * 
 */
typedef npy_intp __pyx_t_5numpy_intp_t;

/* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":759
 * 
 * ctypedef npy_intp       intp_t
 * ctypedef npy_uintp      uintp_t             # <<<<<<<<<<<<<<
 * 
 * ctypedef npy_double     float_t
 */
typedef npy_uintp __pyx_t_5numpy_uintp_t;

/* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":761
 * ctypedef npy_uintp      uintp_t
 * 
 * ctypedef npy_double     float_t             # <<<<<<<<<<<<<<
 * ctypedef npy_double     double_t
 * ctypedef npy_longdouble longdouble_t
 */
typedef npy_double __pyx_t_5numpy_float_t;

/* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":762
 * 
 * ctypedef npy_double     float_t
 * ctypedef npy_double     double_t             # <<<<<<<<<<<<<<
 * ctypedef npy_longdouble longdouble_t
 * 
 */
typedef npy_double __pyx_t_5numpy_double_t;

/* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":763
 * ctypedef npy_double     float_t
 * ctypedef npy_double     double_t
 * ctypedef npy_longdouble longdouble_t             # <<<<<<<<<<<<<<
 * 
 * ctypedef npy_cfloat      cfloat_t
 */
typedef npy_longdouble __pyx_t_5numpy_longdouble_t;
#if CYTHON_CCOMPLEX
  #ifdef __cplusplus
    typedef ::std::complex< double > __pyx_t_double_complex;
  #else
    typedef double _Complex __pyx_t_double_complex;
  #endif
#else
    typedef struct { double real, imag; } __pyx_t_double_complex;
#endif

#if CYTHON_CCOMPLEX
  #ifdef __cplusplus
    typedef ::std::complex< float > __pyx_t_float_complex;
  #else
    typedef float _Complex __pyx_t_float_complex;
  #endif
#else
    typedef struct { float real, imag; } __pyx_t_float_complex;
#endif


/*--- Type declarations ---*/
struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sStatespace;
struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter;
struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zStatespace;
struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter;
struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dStatespace;
struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter;
struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cStatespace;
struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter;
struct __pyx_array_obj;
struct __pyx_MemviewEnum_obj;
struct __pyx_memoryview_obj;
struct __pyx_memoryviewslice_obj;

/* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":765
 * ctypedef npy_longdouble longdouble_t
 * 
 * ctypedef npy_cfloat      cfloat_t             # <<<<<<<<<<<<<<
 * ctypedef npy_cdouble     cdouble_t
 * ctypedef npy_clongdouble clongdouble_t
 */
typedef npy_cfloat __pyx_t_5numpy_cfloat_t;

/* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":766
 * 
 * ctypedef npy_cfloat      cfloat_t
 * ctypedef npy_cdouble     cdouble_t             # <<<<<<<<<<<<<<
 * ctypedef npy_clongdouble clongdouble_t
 * 
 */
typedef npy_cdouble __pyx_t_5numpy_cdouble_t;

/* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":767
 * ctypedef npy_cfloat      cfloat_t
 * ctypedef npy_cdouble     cdouble_t
 * ctypedef npy_clongdouble clongdouble_t             # <<<<<<<<<<<<<<
 * 
 * ctypedef npy_cdouble     complex_t
 */
typedef npy_clongdouble __pyx_t_5numpy_clongdouble_t;

/* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":769
 * ctypedef npy_clongdouble clongdouble_t
 * 
 * ctypedef npy_cdouble     complex_t             # <<<<<<<<<<<<<<
 * 
 * cdef inline object PyArray_MultiIterNew1(a):
 */
typedef npy_cdouble __pyx_t_5numpy_complex_t;

/* "statsmodels\src\blas_lapack.pxd":7
 * #
 * 
 * ctypedef int sgemm_t(             # <<<<<<<<<<<<<<
 *     # Compute C := alpha*A*B + beta*C
 *     char *transa,         # {'T','C'}: o(A)=A'; {'N'}: o(A)=A
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_sgemm_t(char *, char *, int *, int *, int *, __pyx_t_5numpy_float32_t *, __pyx_t_5numpy_float32_t *, int *, __pyx_t_5numpy_float32_t *, int *, __pyx_t_5numpy_float32_t *, __pyx_t_5numpy_float32_t *, int *);

/* "statsmodels\src\blas_lapack.pxd":24
 * )
 * 
 * ctypedef int sgemv_t(             # <<<<<<<<<<<<<<
 *     # Compute C := alpha*A*x + beta*y
 *     char *trans,          # {'T','C'}: o(A)=A'; {'N'}: o(A)=A
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_sgemv_t(char *, int *, int *, __pyx_t_5numpy_float32_t *, __pyx_t_5numpy_float32_t *, int *, __pyx_t_5numpy_float32_t *, int *, __pyx_t_5numpy_float32_t *, __pyx_t_5numpy_float32_t *, int *);

/* "statsmodels\src\blas_lapack.pxd":39
 * )
 * 
 * ctypedef int ssymm_t(             # <<<<<<<<<<<<<<
 *     # SSYMM - perform one of the matrix-matrix operations   C :=
 *     # alpha*A*B + beta*C,
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_ssymm_t(char *, char *, int *, int *, __pyx_t_5numpy_float32_t *, __pyx_t_5numpy_float32_t *, int *, __pyx_t_5numpy_float32_t *, int *, __pyx_t_5numpy_float32_t *, __pyx_t_5numpy_float32_t *, int *);

/* "statsmodels\src\blas_lapack.pxd":56
 * )
 * 
 * ctypedef int ssymv_t(             # <<<<<<<<<<<<<<
 *     # SSYMV - perform the matrix-vector operation   y := alpha*A*x
 *     # + beta*y,
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_ssymv_t(char *, int *, __pyx_t_5numpy_float32_t *, __pyx_t_5numpy_float32_t *, int *, __pyx_t_5numpy_float32_t *, int *, __pyx_t_5numpy_float32_t *, __pyx_t_5numpy_float32_t *, int *);

/* "statsmodels\src\blas_lapack.pxd":71
 * )
 * 
 * ctypedef int strmm_t(             # <<<<<<<<<<<<<<
 *     # STRMM - perform one of the matrix-matrix operations   B :=
 *     # alpha*op( A )*B, or B := alpha*B*op( A ),
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_strmm_t(char *, char *, char *, char *, int *, int *, __pyx_t_5numpy_float32_t *, __pyx_t_5numpy_float32_t *, int *, __pyx_t_5numpy_float32_t *, int *);

/* "statsmodels\src\blas_lapack.pxd":87
 * )
 * 
 * ctypedef int strmv_t(             # <<<<<<<<<<<<<<
 *     # STRMV - perform one of the matrix-vector operations   x :=
 *     # A*x, or x := A'*x,
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_strmv_t(char *, char *, char *, int *, __pyx_t_5numpy_float32_t *, int *, __pyx_t_5numpy_float32_t *, int *);

/* "statsmodels\src\blas_lapack.pxd":100
 * )
 * 
 * ctypedef int scopy_t(             # <<<<<<<<<<<<<<
 *     int *n,           # Number of vector elements to be copied.
 *     np.float32_t *x,  # Vector from which to copy.
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_scopy_t(int *, __pyx_t_5numpy_float32_t *, int *, __pyx_t_5numpy_float32_t *, int *);

/* "statsmodels\src\blas_lapack.pxd":108
 * )
 * 
 * ctypedef int sscal_t(             # <<<<<<<<<<<<<<
 *     # SSCAL - BLAS level one, scales a double precision vector
 *     int *n,               # Number of elements in the vector.
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_sscal_t(int *, __pyx_t_5numpy_float32_t *, __pyx_t_5numpy_float32_t *, int *);

/* "statsmodels\src\blas_lapack.pxd":116
 * )
 * 
 * ctypedef int saxpy_t(             # <<<<<<<<<<<<<<
 *     # Compute y := alpha*x + y
 *     int *n,               # Columns of o(A) / min(len(x))
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_saxpy_t(int *, __pyx_t_5numpy_float32_t *, __pyx_t_5numpy_float32_t *, int *, __pyx_t_5numpy_float32_t *, int *);

/* "statsmodels\src\blas_lapack.pxd":126
 * )
 * 
 * ctypedef np.float64_t sdot_t(             # <<<<<<<<<<<<<<
 *     # Compute DDOT := x.T * y
 *     int *n,           # Length of vectors
 */
typedef __pyx_t_5numpy_float64_t __pyx_t_11statsmodels_3src_11blas_lapack_sdot_t(int *, __pyx_t_5numpy_float32_t *, int *, __pyx_t_5numpy_float32_t *, int *);

/* "statsmodels\src\blas_lapack.pxd":135
 * )
 * 
 * ctypedef int dgemm_t(             # <<<<<<<<<<<<<<
 *     # Compute C := alpha*A*B + beta*C
 *     char *transa,        # {'T','C'}: o(A)=A'; {'N'}: o(A)=A
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_dgemm_t(char *, char *, int *, int *, int *, __pyx_t_5numpy_float64_t *, __pyx_t_5numpy_float64_t *, int *, __pyx_t_5numpy_float64_t *, int *, __pyx_t_5numpy_float64_t *, __pyx_t_5numpy_float64_t *, int *);

/* "statsmodels\src\blas_lapack.pxd":152
 * )
 * 
 * ctypedef int dgemv_t(             # <<<<<<<<<<<<<<
 *     # Compute y := alpha*A*x + beta*y
 *     char *trans,         # {'T','C'}: o(A)=A'; {'N'}: o(A)=A
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_dgemv_t(char *, int *, int *, __pyx_t_5numpy_float64_t *, __pyx_t_5numpy_float64_t *, int *, __pyx_t_5numpy_float64_t *, int *, __pyx_t_5numpy_float64_t *, __pyx_t_5numpy_float64_t *, int *);

/* "statsmodels\src\blas_lapack.pxd":167
 * )
 * 
 * ctypedef int dsymm_t(             # <<<<<<<<<<<<<<
 *     # DSYMM - perform one of the matrix-matrix operations   C :=
 *     # alpha*A*B + beta*C,
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_dsymm_t(char *, char *, int *, int *, __pyx_t_5numpy_float64_t *, __pyx_t_5numpy_float64_t *, int *, __pyx_t_5numpy_float64_t *, int *, __pyx_t_5numpy_float64_t *, __pyx_t_5numpy_float64_t *, int *);

/* "statsmodels\src\blas_lapack.pxd":184
 * )
 * 
 * ctypedef int dsymv_t(             # <<<<<<<<<<<<<<
 *     # DSYMV - perform the matrix-vector operation   y := alpha*A*x
 *     # + beta*y,
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_dsymv_t(char *, int *, __pyx_t_5numpy_float64_t *, __pyx_t_5numpy_float64_t *, int *, __pyx_t_5numpy_float64_t *, int *, __pyx_t_5numpy_float64_t *, __pyx_t_5numpy_float64_t *, int *);

/* "statsmodels\src\blas_lapack.pxd":199
 * )
 * 
 * ctypedef int dtrmm_t(             # <<<<<<<<<<<<<<
 *     # DTRMM - perform one of the matrix-matrix operations   B :=
 *     # alpha*op( A )*B, or B := alpha*B*op( A ),
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_dtrmm_t(char *, char *, char *, char *, int *, int *, __pyx_t_5numpy_float64_t *, __pyx_t_5numpy_float64_t *, int *, __pyx_t_5numpy_float64_t *, int *);

/* "statsmodels\src\blas_lapack.pxd":215
 * )
 * 
 * ctypedef int dtrmv_t(             # <<<<<<<<<<<<<<
 *     # DTRMV - perform one of the matrix-vector operations   x :=
 *     # A*x, or x := A'*x,
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_dtrmv_t(char *, char *, char *, int *, __pyx_t_5numpy_float64_t *, int *, __pyx_t_5numpy_float64_t *, int *);

/* "statsmodels\src\blas_lapack.pxd":228
 * )
 * 
 * ctypedef int dcopy_t(             # <<<<<<<<<<<<<<
 *     int *n,              # Number of vector elements to be copied.
 *     np.float64_t *x,     # Vector from which to copy.
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_dcopy_t(int *, __pyx_t_5numpy_float64_t *, int *, __pyx_t_5numpy_float64_t *, int *);

/* "statsmodels\src\blas_lapack.pxd":236
 * )
 * 
 * ctypedef int dscal_t(             # <<<<<<<<<<<<<<
 *     # DSCAL - BLAS level one, scales a double precision vector
 *     int *n,               # Number of elements in the vector.
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_dscal_t(int *, __pyx_t_5numpy_float64_t *, __pyx_t_5numpy_float64_t *, int *);

/* "statsmodels\src\blas_lapack.pxd":244
 * )
 * 
 * ctypedef int daxpy_t(             # <<<<<<<<<<<<<<
 *     # Compute y := alpha*x + y
 *     int *n,              # Columns of o(A) / min(len(x))
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_daxpy_t(int *, __pyx_t_5numpy_float64_t *, __pyx_t_5numpy_float64_t *, int *, __pyx_t_5numpy_float64_t *, int *);

/* "statsmodels\src\blas_lapack.pxd":254
 * )
 * 
 * ctypedef double ddot_t(             # <<<<<<<<<<<<<<
 *     # Compute DDOT := x.T * y
 *     int *n,              # Length of vectors
 */
typedef double __pyx_t_11statsmodels_3src_11blas_lapack_ddot_t(int *, __pyx_t_5numpy_float64_t *, int *, __pyx_t_5numpy_float64_t *, int *);

/* "statsmodels\src\blas_lapack.pxd":263
 * )
 * 
 * ctypedef int cgemm_t(             # <<<<<<<<<<<<<<
 *     # Compute C := alpha*A*B + beta*C
 *     char *transa,           # {'T','C'}: o(A)=A'; {'N'}: o(A)=A
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_cgemm_t(char *, char *, int *, int *, int *, __pyx_t_float_complex *, __pyx_t_float_complex *, int *, __pyx_t_float_complex *, int *, __pyx_t_float_complex *, __pyx_t_float_complex *, int *);

/* "statsmodels\src\blas_lapack.pxd":280
 * )
 * 
 * ctypedef int cgemv_t(             # <<<<<<<<<<<<<<
 *     # Compute C := alpha*A*x + beta*y
 *     char *trans,            # {'T','C'}: o(A)=A'; {'N'}: o(A)=A
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_cgemv_t(char *, int *, int *, __pyx_t_float_complex *, __pyx_t_float_complex *, int *, __pyx_t_float_complex *, int *, __pyx_t_float_complex *, __pyx_t_float_complex *, int *);

/* "statsmodels\src\blas_lapack.pxd":295
 * )
 * 
 * ctypedef int csymm_t(             # <<<<<<<<<<<<<<
 *     # CSYMM - perform one of the matrix-matrix operations   C :=
 *     # alpha*A*B + beta*C,
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_csymm_t(char *, char *, int *, int *, __pyx_t_float_complex *, __pyx_t_float_complex *, int *, __pyx_t_float_complex *, int *, __pyx_t_float_complex *, __pyx_t_float_complex *, int *);

/* "statsmodels\src\blas_lapack.pxd":312
 * )
 * 
 * ctypedef int csymv_t(             # <<<<<<<<<<<<<<
 *     # CSYMV - perform the matrix-vector operation   y := alpha*A*x
 *     # + beta*y,
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_csymv_t(char *, int *, __pyx_t_float_complex *, __pyx_t_float_complex *, int *, __pyx_t_float_complex *, int *, __pyx_t_float_complex *, __pyx_t_float_complex *, int *);

/* "statsmodels\src\blas_lapack.pxd":327
 * )
 * 
 * ctypedef int ctrmm_t(             # <<<<<<<<<<<<<<
 *     # CTRMM - perform one of the matrix-matrix operations   B :=
 *     # alpha*op( A )*B, or B := alpha*B*op( A ),
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_ctrmm_t(char *, char *, char *, char *, int *, int *, __pyx_t_float_complex *, __pyx_t_float_complex *, int *, __pyx_t_float_complex *, int *);

/* "statsmodels\src\blas_lapack.pxd":343
 * )
 * 
 * ctypedef int ctrmv_t(             # <<<<<<<<<<<<<<
 *     # CTRMV - perform one of the matrix-vector operations   x :=
 *     # A*x, or x := A'*x,
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_ctrmv_t(char *, char *, char *, int *, __pyx_t_float_complex *, int *, __pyx_t_float_complex *, int *);

/* "statsmodels\src\blas_lapack.pxd":356
 * )
 * 
 * ctypedef int ccopy_t(             # <<<<<<<<<<<<<<
 *     int *n,             # Number of vector elements to be copied.
 *     np.complex64_t *x,  # Vector from which to copy.
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_ccopy_t(int *, __pyx_t_float_complex *, int *, __pyx_t_float_complex *, int *);

/* "statsmodels\src\blas_lapack.pxd":364
 * )
 * 
 * ctypedef int cscal_t(             # <<<<<<<<<<<<<<
 *     # CSCAL - BLAS level one, scales a double precision vector
 *     int *n,                 # Number of elements in the vector.
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_cscal_t(int *, __pyx_t_float_complex *, __pyx_t_float_complex *, int *);

/* "statsmodels\src\blas_lapack.pxd":372
 * )
 * 
 * ctypedef int caxpy_t(             # <<<<<<<<<<<<<<
 *     # Compute y := alpha*x + y
 *     int *n,                 # Columns of o(A) / min(len(x))
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_caxpy_t(int *, __pyx_t_float_complex *, __pyx_t_float_complex *, int *, __pyx_t_float_complex *, int *);

/* "statsmodels\src\blas_lapack.pxd":382
 * )
 * 
 * ctypedef np.complex64_t cdotu_t(             # <<<<<<<<<<<<<<
 *     # Compute CDOTU := x.T * y
 *     int *n,             # Length of vectors
 */
typedef __pyx_t_float_complex __pyx_t_11statsmodels_3src_11blas_lapack_cdotu_t(int *, __pyx_t_float_complex *, int *, __pyx_t_float_complex *, int *);

/* "statsmodels\src\blas_lapack.pxd":391
 * )
 * 
 * ctypedef int zgemm_t(             # <<<<<<<<<<<<<<
 *     # Compute C := alpha*A*B + beta*C
 *     char *transa,           # {'T','C'}: o(A)=A'; {'N'}: o(A)=A
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_zgemm_t(char *, char *, int *, int *, int *, __pyx_t_double_complex *, __pyx_t_double_complex *, int *, __pyx_t_double_complex *, int *, __pyx_t_double_complex *, __pyx_t_double_complex *, int *);

/* "statsmodels\src\blas_lapack.pxd":408
 * )
 * 
 * ctypedef int zgemv_t(             # <<<<<<<<<<<<<<
 *     # Compute C := alpha*A*x + beta*y
 *     char *trans,    # {'T','C'}: o(A)=A'; {'N'}: o(A)=A
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_zgemv_t(char *, int *, int *, __pyx_t_double_complex *, __pyx_t_double_complex *, int *, __pyx_t_double_complex *, int *, __pyx_t_double_complex *, __pyx_t_double_complex *, int *);

/* "statsmodels\src\blas_lapack.pxd":423
 * )
 * 
 * ctypedef int zsymm_t(             # <<<<<<<<<<<<<<
 *     # ZSYMM - perform one of the matrix-matrix operations   C :=
 *     # alpha*A*B + beta*C,
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_zsymm_t(char *, char *, int *, int *, __pyx_t_double_complex *, __pyx_t_double_complex *, int *, __pyx_t_double_complex *, int *, __pyx_t_double_complex *, __pyx_t_double_complex *, int *);

/* "statsmodels\src\blas_lapack.pxd":440
 * )
 * 
 * ctypedef int zsymv_t(             # <<<<<<<<<<<<<<
 *     # ZSYMV - perform the matrix-vector operation   y := alpha*A*x
 *     # + beta*y,
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_zsymv_t(char *, int *, __pyx_t_double_complex *, __pyx_t_double_complex *, int *, __pyx_t_double_complex *, int *, __pyx_t_double_complex *, __pyx_t_double_complex *, int *);

/* "statsmodels\src\blas_lapack.pxd":455
 * )
 * 
 * ctypedef int ztrmm_t(             # <<<<<<<<<<<<<<
 *     # ZTRMM - perform one of the matrix-matrix operations   B :=
 *     # alpha*op( A )*B, or B := alpha*B*op( A ),
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_ztrmm_t(char *, char *, char *, char *, int *, int *, __pyx_t_double_complex *, __pyx_t_double_complex *, int *, __pyx_t_double_complex *, int *);

/* "statsmodels\src\blas_lapack.pxd":471
 * )
 * 
 * ctypedef int ztrmv_t(             # <<<<<<<<<<<<<<
 *     # ZTRMV - perform one of the matrix-vector operations   x :=
 *     # A*x, or x := A'*x,
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_ztrmv_t(char *, char *, char *, int *, __pyx_t_double_complex *, int *, __pyx_t_double_complex *, int *);

/* "statsmodels\src\blas_lapack.pxd":484
 * )
 * 
 * ctypedef int zcopy_t(             # <<<<<<<<<<<<<<
 *     int *n,         # Number of vector elements to be copied.
 *     np.complex128_t *x,     # Vector from which to copy.
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_zcopy_t(int *, __pyx_t_double_complex *, int *, __pyx_t_double_complex *, int *);

/* "statsmodels\src\blas_lapack.pxd":492
 * )
 * 
 * ctypedef int zscal_t(             # <<<<<<<<<<<<<<
 *     # ZSCAL - BLAS level one, scales a double np.complex128_t precision vector
 *     int *n,          # Number of elements in the vector.
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_zscal_t(int *, __pyx_t_double_complex *, __pyx_t_double_complex *, int *);

/* "statsmodels\src\blas_lapack.pxd":500
 * )
 * 
 * ctypedef int zaxpy_t(             # <<<<<<<<<<<<<<
 *     # Compute y := alpha*x + y
 *     int *n,         # Columns of o(A) / min(len(x))
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_zaxpy_t(int *, __pyx_t_double_complex *, __pyx_t_double_complex *, int *, __pyx_t_double_complex *, int *);

/* "statsmodels\src\blas_lapack.pxd":510
 * )
 * 
 * ctypedef np.complex128_t zdotu_t(             # <<<<<<<<<<<<<<
 *     # Compute ZDOTU := x.T * y
 *     int *n,      # Length of vectors
 */
typedef __pyx_t_double_complex __pyx_t_11statsmodels_3src_11blas_lapack_zdotu_t(int *, __pyx_t_double_complex *, int *, __pyx_t_double_complex *, int *);

/* "statsmodels\src\blas_lapack.pxd":523
 * #
 * 
 * ctypedef int sgetrf_t(             # <<<<<<<<<<<<<<
 *     # SGETRF - compute an LU factorization of a general M-by-N
 *     # matrix A using partial pivoting with row interchanges
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_sgetrf_t(int *, int *, __pyx_t_5numpy_float32_t *, int *, int *, int *);

/* "statsmodels\src\blas_lapack.pxd":534
 * )
 * 
 * ctypedef int sgetri_t(             # <<<<<<<<<<<<<<
 *     # SGETRI - compute the inverse of a matrix using the LU fac-
 *     # torization computed by SGETRF
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_sgetri_t(int *, __pyx_t_5numpy_float32_t *, int *, int *, __pyx_t_5numpy_float32_t *, int *, int *);

/* "statsmodels\src\blas_lapack.pxd":546
 * )
 * 
 * ctypedef int sgetrs_t(             # <<<<<<<<<<<<<<
 *     # SGETRS - solve a system of linear equations  A * X = B or A'
 *     # * X = B with a general N-by-N matrix A using the LU factori-
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_sgetrs_t(char *, int *, int *, __pyx_t_5numpy_float32_t *, int *, int *, __pyx_t_5numpy_float32_t *, int *, int *);

/* "statsmodels\src\blas_lapack.pxd":561
 * )
 * 
 * ctypedef int spotrf_t(             # <<<<<<<<<<<<<<
 *     # Compute the Cholesky factorization of a
 *     # real  symmetric positive definite matrix A
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_spotrf_t(char *, int *, __pyx_t_5numpy_float32_t *, int *, int *);

/* "statsmodels\src\blas_lapack.pxd":571
 * )
 * 
 * ctypedef int spotri_t(             # <<<<<<<<<<<<<<
 *     # SPOTRI - compute the inverse of a real symmetric positive
 *     # definite matrix A using the Cholesky factorization A =
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_spotri_t(char *, int *, __pyx_t_5numpy_float32_t *, int *, int *);

/* "statsmodels\src\blas_lapack.pxd":582
 * )
 * 
 * ctypedef int spotrs_t(             # <<<<<<<<<<<<<<
 *     # SPOTRS - solve a system of linear equations A*X = B with a
 *     # symmetric positive definite matrix A using the Cholesky fac-
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_spotrs_t(char *, int *, int *, __pyx_t_5numpy_float32_t *, int *, __pyx_t_5numpy_float32_t *, int *, int *);

/* "statsmodels\src\blas_lapack.pxd":596
 * )
 * 
 * ctypedef int strtrs_t(             # <<<<<<<<<<<<<<
 *     #  STRTRS solves a triangular system of the form
 *     #      A * X = B,  A**T * X = B,  or  A**H * X = B,
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_strtrs_t(char *, char *, char *, int *, int *, __pyx_t_5numpy_float32_t *, int *, __pyx_t_5numpy_float32_t *, int *, int *);

/* "statsmodels\src\blas_lapack.pxd":613
 * )
 * 
 * ctypedef int dgetrf_t(             # <<<<<<<<<<<<<<
 *     # DGETRF - compute an LU factorization of a general M-by-N
 *     # matrix A using partial pivoting with row interchanges
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_dgetrf_t(int *, int *, __pyx_t_5numpy_float64_t *, int *, int *, int *);

/* "statsmodels\src\blas_lapack.pxd":624
 * )
 * 
 * ctypedef int dgetri_t(             # <<<<<<<<<<<<<<
 *     # DGETRI - compute the inverse of a matrix using the LU fac-
 *     # torization computed by DGETRF
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_dgetri_t(int *, __pyx_t_5numpy_float64_t *, int *, int *, __pyx_t_5numpy_float64_t *, int *, int *);

/* "statsmodels\src\blas_lapack.pxd":636
 * )
 * 
 * ctypedef int dgetrs_t(             # <<<<<<<<<<<<<<
 *     # DGETRS - solve a system of linear equations  A * X = B or A'
 *     # * X = B with a general N-by-N matrix A using the LU factori-
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_dgetrs_t(char *, int *, int *, __pyx_t_5numpy_float64_t *, int *, int *, __pyx_t_5numpy_float64_t *, int *, int *);

/* "statsmodels\src\blas_lapack.pxd":651
 * )
 * 
 * ctypedef int dpotrf_t(             # <<<<<<<<<<<<<<
 *     # Compute the Cholesky factorization of a
 *     # real  symmetric positive definite matrix A
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_dpotrf_t(char *, int *, __pyx_t_5numpy_float64_t *, int *, int *);

/* "statsmodels\src\blas_lapack.pxd":661
 * )
 * 
 * ctypedef int dpotri_t(             # <<<<<<<<<<<<<<
 *     # DPOTRI - compute the inverse of a real symmetric positive
 *     # definite matrix A using the Cholesky factorization A =
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_dpotri_t(char *, int *, __pyx_t_5numpy_float64_t *, int *, int *);

/* "statsmodels\src\blas_lapack.pxd":672
 * )
 * 
 * ctypedef int dpotrs_t(             # <<<<<<<<<<<<<<
 *     # DPOTRS - solve a system of linear equations A*X = B with a
 *     # symmetric positive definite matrix A using the Cholesky fac-
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_dpotrs_t(char *, int *, int *, __pyx_t_5numpy_float64_t *, int *, __pyx_t_5numpy_float64_t *, int *, int *);

/* "statsmodels\src\blas_lapack.pxd":686
 * )
 * 
 * ctypedef int dtrtrs_t(             # <<<<<<<<<<<<<<
 *     #  DTRTRS solves a triangular system of the form
 *     #      A * X = B,  A**T * X = B,  or  A**H * X = B,
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_dtrtrs_t(char *, char *, char *, int *, int *, __pyx_t_5numpy_float64_t *, int *, __pyx_t_5numpy_float64_t *, int *, int *);

/* "statsmodels\src\blas_lapack.pxd":703
 * )
 * 
 * ctypedef int cgetrf_t(             # <<<<<<<<<<<<<<
 *     # CGETRF - compute an LU factorization of a general M-by-N
 *     # matrix A using partial pivoting with row interchanges
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_cgetrf_t(int *, int *, __pyx_t_float_complex *, int *, int *, int *);

/* "statsmodels\src\blas_lapack.pxd":714
 * )
 * 
 * ctypedef int cgetri_t(             # <<<<<<<<<<<<<<
 *     # CGETRI - compute the inverse of a matrix using the LU fac-
 *     # torization computed by CGETRF
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_cgetri_t(int *, __pyx_t_float_complex *, int *, int *, __pyx_t_float_complex *, int *, int *);

/* "statsmodels\src\blas_lapack.pxd":726
 * )
 * 
 * ctypedef int cgetrs_t(             # <<<<<<<<<<<<<<
 *     # CGETRS - solve a system of linear equations  A * X = B, A**T
 *     # * X = B, or A**H * X = B with a general N-by-N matrix A
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_cgetrs_t(char *, int *, int *, __pyx_t_float_complex *, int *, int *, __pyx_t_float_complex *, int *, int *);

/* "statsmodels\src\blas_lapack.pxd":741
 * )
 * 
 * ctypedef int cpotrf_t(             # <<<<<<<<<<<<<<
 *     # Compute the Cholesky factorization of a
 *     # np.complex128_t Hermitian positive definite matrix A
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_cpotrf_t(char *, int *, __pyx_t_float_complex *, int *, int *);

/* "statsmodels\src\blas_lapack.pxd":751
 * )
 * 
 * ctypedef int cpotri_t(             # <<<<<<<<<<<<<<
 *     # CPOTRI - compute the inverse of a np.complex128_t Hermitian positive
 *     # definite matrix A using the Cholesky factorization A =
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_cpotri_t(char *, int *, __pyx_t_float_complex *, int *, int *);

/* "statsmodels\src\blas_lapack.pxd":762
 * )
 * 
 * ctypedef int cpotrs_t(             # <<<<<<<<<<<<<<
 *     # ZPOTRS - solve a system of linear equations A*X = B with a
 *     # Hermitian positive definite matrix A using the Cholesky fac-
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_cpotrs_t(char *, int *, int *, __pyx_t_float_complex *, int *, __pyx_t_float_complex *, int *, int *);

/* "statsmodels\src\blas_lapack.pxd":776
 * )
 * 
 * ctypedef int ctrtrs_t(             # <<<<<<<<<<<<<<
 *     #  CTRTRS solves a triangular system of the form
 *     #      A * X = B,  A**T * X = B,  or  A**H * X = B,
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_ctrtrs_t(char *, char *, char *, int *, int *, __pyx_t_float_complex *, int *, __pyx_t_float_complex *, int *, int *);

/* "statsmodels\src\blas_lapack.pxd":793
 * )
 * 
 * ctypedef int zgetrf_t(             # <<<<<<<<<<<<<<
 *     # ZGETRF - compute an LU factorization of a general M-by-N
 *     # matrix A using partial pivoting with row interchanges
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_zgetrf_t(int *, int *, __pyx_t_double_complex *, int *, int *, int *);

/* "statsmodels\src\blas_lapack.pxd":804
 * )
 * 
 * ctypedef int zgetri_t(             # <<<<<<<<<<<<<<
 *     # ZGETRI - compute the inverse of a matrix using the LU fac-
 *     # torization computed by ZGETRF
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_zgetri_t(int *, __pyx_t_double_complex *, int *, int *, __pyx_t_double_complex *, int *, int *);

/* "statsmodels\src\blas_lapack.pxd":816
 * )
 * 
 * ctypedef int zgetrs_t(             # <<<<<<<<<<<<<<
 *     # ZGETRS - solve a system of linear equations  A * X = B, A**T
 *     # * X = B, or A**H * X = B with a general N-by-N matrix A
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_zgetrs_t(char *, int *, int *, __pyx_t_double_complex *, int *, int *, __pyx_t_double_complex *, int *, int *);

/* "statsmodels\src\blas_lapack.pxd":831
 * )
 * 
 * ctypedef int zpotrf_t(             # <<<<<<<<<<<<<<
 *     # Compute the Cholesky factorization of a
 *     # np.complex128_t Hermitian positive definite matrix A
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_zpotrf_t(char *, int *, __pyx_t_double_complex *, int *, int *);

/* "statsmodels\src\blas_lapack.pxd":841
 * )
 * 
 * ctypedef int zpotri_t(             # <<<<<<<<<<<<<<
 *     # ZPOTRI - compute the inverse of a np.complex128_t Hermitian positive
 *     # definite matrix A using the Cholesky factorization A =
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_zpotri_t(char *, int *, __pyx_t_double_complex *, int *, int *);

/* "statsmodels\src\blas_lapack.pxd":852
 * )
 * 
 * ctypedef int zpotrs_t(             # <<<<<<<<<<<<<<
 *     # ZPOTRS - solve a system of linear equations A*X = B with a
 *     # Hermitian positive definite matrix A using the Cholesky fac-
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_zpotrs_t(char *, int *, int *, __pyx_t_double_complex *, int *, __pyx_t_double_complex *, int *, int *);

/* "statsmodels\src\blas_lapack.pxd":866
 * )
 * 
 * ctypedef int ztrtrs_t(             # <<<<<<<<<<<<<<
 *     #  ZTRTRS solves a triangular system of the form
 *     #      A * X = B,  A**T * X = B,  or  A**H * X = B,
 */
typedef int __pyx_t_11statsmodels_3src_11blas_lapack_ztrtrs_t(char *, char *, char *, int *, int *, __pyx_t_double_complex *, int *, __pyx_t_double_complex *, int *, int *);
struct __pyx_opt_args_11statsmodels_3tsa_10statespace_11_statespace_validate_matrix_shape;
struct __pyx_opt_args_11statsmodels_3tsa_10statespace_11_statespace_validate_vector_shape;
struct __pyx_opt_args_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_set_filter_method;
struct __pyx_opt_args_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_seek;
struct __pyx_opt_args_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_set_filter_method;
struct __pyx_opt_args_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_seek;
struct __pyx_opt_args_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_set_filter_method;
struct __pyx_opt_args_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_seek;
struct __pyx_opt_args_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_set_filter_method;
struct __pyx_opt_args_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_seek;

/* "statsmodels\tsa\statespace\_statespace.pyx":156
 * 
 * # Array shape validation
 * cdef validate_matrix_shape(str name, Py_ssize_t *shape, int nrows, int ncols, nobs=None):             # <<<<<<<<<<<<<<
 *     if not shape[0] == nrows:
 *         raise ValueError('Invalid shape for %s matrix: requires %d rows,'
 */
struct __pyx_opt_args_11statsmodels_3tsa_10statespace_11_statespace_validate_matrix_shape {
  int __pyx_n;
  PyObject *nobs;
};

/* "statsmodels\tsa\statespace\_statespace.pyx":167
 *                          ' requires 1 or %d, got %d' % (name, nobs, shape[2]))
 * 
 * cdef validate_vector_shape(str name, Py_ssize_t *shape, int nrows, nobs = None):             # <<<<<<<<<<<<<<
 *     if not shape[0] == nrows:
 *         raise ValueError('Invalid shape for %s vector: requires %d rows,'
 */
struct __pyx_opt_args_11statsmodels_3tsa_10statespace_11_statespace_validate_vector_shape {
  int __pyx_n;
  PyObject *nobs;
};

/* "statsmodels\tsa\statespace\_statespace.pyx":1323
 *         self.period_converged = 0
 * 
 *     cpdef set_filter_method(self, int filter_method, int force_reset=True):             # <<<<<<<<<<<<<<
 *         """
 *         set_filter_method(self, filter_method, force_reset=True)
 */
struct __pyx_opt_args_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_set_filter_method {
  int __pyx_n;
  int force_reset;
};

/* "statsmodels\tsa\statespace\_statespace.pyx":1331
 *         self.filter_method = filter_method
 * 
 *     cpdef seek(self, unsigned int t, int reset_convergence = True):             # <<<<<<<<<<<<<<
 *         """
 *         seek(self, t, reset_convergence = True)
 */
struct __pyx_opt_args_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_seek {
  int __pyx_n;
  int reset_convergence;
};

/* "statsmodels\tsa\statespace\_statespace.pyx":3260
 *         self.period_converged = 0
 * 
 *     cpdef set_filter_method(self, int filter_method, int force_reset=True):             # <<<<<<<<<<<<<<
 *         """
 *         set_filter_method(self, filter_method, force_reset=True)
 */
struct __pyx_opt_args_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_set_filter_method {
  int __pyx_n;
  int force_reset;
};

/* "statsmodels\tsa\statespace\_statespace.pyx":3268
 *         self.filter_method = filter_method
 * 
 *     cpdef seek(self, unsigned int t, int reset_convergence = True):             # <<<<<<<<<<<<<<
 *         """
 *         seek(self, t, reset_convergence = True)
 */
struct __pyx_opt_args_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_seek {
  int __pyx_n;
  int reset_convergence;
};

/* "statsmodels\tsa\statespace\_statespace.pyx":5193
 *         self.period_converged = 0
 * 
 *     cpdef set_filter_method(self, int filter_method, int force_reset=True):             # <<<<<<<<<<<<<<
 *         """
 *         set_filter_method(self, filter_method, force_reset=True)
 */
struct __pyx_opt_args_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_set_filter_method {
  int __pyx_n;
  int force_reset;
};

/* "statsmodels\tsa\statespace\_statespace.pyx":5201
 *         self.filter_method = filter_method
 * 
 *     cpdef seek(self, unsigned int t, int reset_convergence = True):             # <<<<<<<<<<<<<<
 *         """
 *         seek(self, t, reset_convergence = True)
 */
struct __pyx_opt_args_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_seek {
  int __pyx_n;
  int reset_convergence;
};

/* "statsmodels\tsa\statespace\_statespace.pyx":7130
 *         self.period_converged = 0
 * 
 *     cpdef set_filter_method(self, int filter_method, int force_reset=True):             # <<<<<<<<<<<<<<
 *         """
 *         set_filter_method(self, filter_method, force_reset=True)
 */
struct __pyx_opt_args_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_set_filter_method {
  int __pyx_n;
  int force_reset;
};

/* "statsmodels\tsa\statespace\_statespace.pyx":7138
 *         self.filter_method = filter_method
 * 
 *     cpdef seek(self, unsigned int t, int reset_convergence = True):             # <<<<<<<<<<<<<<
 *         """
 *         seek(self, t, reset_convergence = True)
 */
struct __pyx_opt_args_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_seek {
  int __pyx_n;
  int reset_convergence;
};

/* "statsmodels\tsa\statespace\_statespace.pyx":176
 * 
 * ## State Space Representation
 * cdef class sStatespace(object):             # <<<<<<<<<<<<<<
 *     """
 *     sStatespace(obs, design, obs_intercept, obs_cov, transition, state_intercept, selection, state_cov)
 */
struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sStatespace {
  PyObject_HEAD
  int nobs;
  int k_endog;
  int k_states;
  int k_posdef;
  __Pyx_memviewslice obs;
  __Pyx_memviewslice obs_intercept;
  __Pyx_memviewslice state_intercept;
  __Pyx_memviewslice initial_state;
  __Pyx_memviewslice initial_state_cov;
  __Pyx_memviewslice design;
  __Pyx_memviewslice obs_cov;
  __Pyx_memviewslice transition;
  __Pyx_memviewslice selection;
  __Pyx_memviewslice state_cov;
  __Pyx_memviewslice selected_state_cov;
  __Pyx_memviewslice missing;
  __Pyx_memviewslice nmissing;
  int time_invariant;
  int initialized;
  __Pyx_memviewslice tmp;
  __pyx_t_5numpy_float32_t *_obs;
  __pyx_t_5numpy_float32_t *_design;
  __pyx_t_5numpy_float32_t *_obs_intercept;
  __pyx_t_5numpy_float32_t *_obs_cov;
  __pyx_t_5numpy_float32_t *_transition;
  __pyx_t_5numpy_float32_t *_state_intercept;
  __pyx_t_5numpy_float32_t *_selection;
  __pyx_t_5numpy_float32_t *_state_cov;
  __pyx_t_5numpy_float32_t *_selected_state_cov;
  __pyx_t_5numpy_float32_t *_initial_state;
  __pyx_t_5numpy_float32_t *_initial_state_cov;
};


/* "statsmodels\tsa\statespace\_statespace.pyx":970
 * # ## Kalman filter
 * 
 * cdef class sKalmanFilter(object):             # <<<<<<<<<<<<<<
 *     """
 *     sKalmanFilter(model, filter=FILTER_CONVENTIONAL, inversion_method=INVERT_UNIVARIATE | SOLVE_CHOLESKY, stability_method=STABILITY_FORCE_SYMMETRY, tolerance=1e-19)
 */
struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter {
  PyObject_HEAD
  struct __pyx_vtabstruct_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_vtab;
  struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sStatespace *model;
  int t;
  __pyx_t_5numpy_float64_t tolerance;
  int converged;
  int period_converged;
  int time_invariant;
  int filter_method;
  int inversion_method;
  int stability_method;
  int conserve_memory;
  int loglikelihood_burn;
  __Pyx_memviewslice loglikelihood;
  __Pyx_memviewslice filtered_state;
  __Pyx_memviewslice predicted_state;
  __Pyx_memviewslice forecast;
  __Pyx_memviewslice forecast_error;
  __Pyx_memviewslice filtered_state_cov;
  __Pyx_memviewslice predicted_state_cov;
  __Pyx_memviewslice forecast_error_cov;
  __Pyx_memviewslice converged_forecast_error_cov;
  __Pyx_memviewslice converged_filtered_state_cov;
  __Pyx_memviewslice converged_predicted_state_cov;
  __pyx_t_5numpy_float32_t converged_determinant;
  __Pyx_memviewslice selected_obs;
  __Pyx_memviewslice selected_design;
  __Pyx_memviewslice selected_obs_cov;
  __Pyx_memviewslice forecast_error_fac;
  __Pyx_memviewslice forecast_error_ipiv;
  __Pyx_memviewslice forecast_error_work;
  __Pyx_memviewslice tmp0;
  __Pyx_memviewslice tmp1;
  __Pyx_memviewslice tmp3;
  __Pyx_memviewslice tmp2;
  __pyx_t_5numpy_float32_t determinant;
  __pyx_t_5numpy_float32_t *_obs;
  __pyx_t_5numpy_float32_t *_design;
  __pyx_t_5numpy_float32_t *_obs_intercept;
  __pyx_t_5numpy_float32_t *_obs_cov;
  __pyx_t_5numpy_float32_t *_transition;
  __pyx_t_5numpy_float32_t *_state_intercept;
  __pyx_t_5numpy_float32_t *_selection;
  __pyx_t_5numpy_float32_t *_state_cov;
  __pyx_t_5numpy_float32_t *_selected_state_cov;
  __pyx_t_5numpy_float32_t *_initial_state;
  __pyx_t_5numpy_float32_t *_initial_state_cov;
  __pyx_t_5numpy_float32_t *_input_state;
  __pyx_t_5numpy_float32_t *_input_state_cov;
  __pyx_t_5numpy_float32_t *_forecast;
  __pyx_t_5numpy_float32_t *_forecast_error;
  __pyx_t_5numpy_float32_t *_forecast_error_cov;
  __pyx_t_5numpy_float32_t *_filtered_state;
  __pyx_t_5numpy_float32_t *_filtered_state_cov;
  __pyx_t_5numpy_float32_t *_predicted_state;
  __pyx_t_5numpy_float32_t *_predicted_state_cov;
  __pyx_t_5numpy_float32_t *_converged_forecast_error_cov;
  __pyx_t_5numpy_float32_t *_converged_filtered_state_cov;
  __pyx_t_5numpy_float32_t *_converged_predicted_state_cov;
  __pyx_t_5numpy_float32_t *_forecast_error_fac;
  int *_forecast_error_ipiv;
  __pyx_t_5numpy_float32_t *_forecast_error_work;
  __pyx_t_5numpy_float32_t *_tmp0;
  __pyx_t_5numpy_float32_t *_tmp1;
  __pyx_t_5numpy_float32_t *_tmp2;
  __pyx_t_5numpy_float32_t *_tmp3;
  int (*forecasting)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *);
  __pyx_t_5numpy_float32_t (*inversion)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *, __pyx_t_5numpy_float32_t);
  int (*updating)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *);
  __pyx_t_5numpy_float32_t (*calculate_loglikelihood)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *, __pyx_t_5numpy_float32_t);
  int (*prediction)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *);
  int k_endog;
  int k_states;
  int k_posdef;
  int k_endog2;
  int k_states2;
  int k_endogstates;
  int ldwork;
};


/* "statsmodels\tsa\statespace\_statespace.pyx":2109
 * 
 * ## State Space Representation
 * cdef class zStatespace(object):             # <<<<<<<<<<<<<<
 *     """
 *     zStatespace(obs, design, obs_intercept, obs_cov, transition, state_intercept, selection, state_cov)
 */
struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zStatespace {
  PyObject_HEAD
  int nobs;
  int k_endog;
  int k_states;
  int k_posdef;
  __Pyx_memviewslice obs;
  __Pyx_memviewslice obs_intercept;
  __Pyx_memviewslice state_intercept;
  __Pyx_memviewslice initial_state;
  __Pyx_memviewslice initial_state_cov;
  __Pyx_memviewslice design;
  __Pyx_memviewslice obs_cov;
  __Pyx_memviewslice transition;
  __Pyx_memviewslice selection;
  __Pyx_memviewslice state_cov;
  __Pyx_memviewslice selected_state_cov;
  __Pyx_memviewslice missing;
  __Pyx_memviewslice nmissing;
  int time_invariant;
  int initialized;
  __Pyx_memviewslice tmp;
  __pyx_t_double_complex *_obs;
  __pyx_t_double_complex *_design;
  __pyx_t_double_complex *_obs_intercept;
  __pyx_t_double_complex *_obs_cov;
  __pyx_t_double_complex *_transition;
  __pyx_t_double_complex *_state_intercept;
  __pyx_t_double_complex *_selection;
  __pyx_t_double_complex *_state_cov;
  __pyx_t_double_complex *_selected_state_cov;
  __pyx_t_double_complex *_initial_state;
  __pyx_t_double_complex *_initial_state_cov;
};


/* "statsmodels\tsa\statespace\_statespace.pyx":2907
 * # ## Kalman filter
 * 
 * cdef class zKalmanFilter(object):             # <<<<<<<<<<<<<<
 *     """
 *     zKalmanFilter(model, filter=FILTER_CONVENTIONAL, inversion_method=INVERT_UNIVARIATE | SOLVE_CHOLESKY, stability_method=STABILITY_FORCE_SYMMETRY, tolerance=1e-19)
 */
struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter {
  PyObject_HEAD
  struct __pyx_vtabstruct_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_vtab;
  struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zStatespace *model;
  int t;
  __pyx_t_5numpy_float64_t tolerance;
  int converged;
  int period_converged;
  int time_invariant;
  int filter_method;
  int inversion_method;
  int stability_method;
  int conserve_memory;
  int loglikelihood_burn;
  __Pyx_memviewslice loglikelihood;
  __Pyx_memviewslice filtered_state;
  __Pyx_memviewslice predicted_state;
  __Pyx_memviewslice forecast;
  __Pyx_memviewslice forecast_error;
  __Pyx_memviewslice filtered_state_cov;
  __Pyx_memviewslice predicted_state_cov;
  __Pyx_memviewslice forecast_error_cov;
  __Pyx_memviewslice converged_forecast_error_cov;
  __Pyx_memviewslice converged_filtered_state_cov;
  __Pyx_memviewslice converged_predicted_state_cov;
  __pyx_t_double_complex converged_determinant;
  __Pyx_memviewslice selected_obs;
  __Pyx_memviewslice selected_design;
  __Pyx_memviewslice selected_obs_cov;
  __Pyx_memviewslice forecast_error_fac;
  __Pyx_memviewslice forecast_error_ipiv;
  __Pyx_memviewslice forecast_error_work;
  __Pyx_memviewslice tmp0;
  __Pyx_memviewslice tmp1;
  __Pyx_memviewslice tmp3;
  __Pyx_memviewslice tmp2;
  __pyx_t_double_complex determinant;
  __pyx_t_double_complex *_obs;
  __pyx_t_double_complex *_design;
  __pyx_t_double_complex *_obs_intercept;
  __pyx_t_double_complex *_obs_cov;
  __pyx_t_double_complex *_transition;
  __pyx_t_double_complex *_state_intercept;
  __pyx_t_double_complex *_selection;
  __pyx_t_double_complex *_state_cov;
  __pyx_t_double_complex *_selected_state_cov;
  __pyx_t_double_complex *_initial_state;
  __pyx_t_double_complex *_initial_state_cov;
  __pyx_t_double_complex *_input_state;
  __pyx_t_double_complex *_input_state_cov;
  __pyx_t_double_complex *_forecast;
  __pyx_t_double_complex *_forecast_error;
  __pyx_t_double_complex *_forecast_error_cov;
  __pyx_t_double_complex *_filtered_state;
  __pyx_t_double_complex *_filtered_state_cov;
  __pyx_t_double_complex *_predicted_state;
  __pyx_t_double_complex *_predicted_state_cov;
  __pyx_t_double_complex *_converged_forecast_error_cov;
  __pyx_t_double_complex *_converged_filtered_state_cov;
  __pyx_t_double_complex *_converged_predicted_state_cov;
  __pyx_t_double_complex *_forecast_error_fac;
  int *_forecast_error_ipiv;
  __pyx_t_double_complex *_forecast_error_work;
  __pyx_t_double_complex *_tmp0;
  __pyx_t_double_complex *_tmp1;
  __pyx_t_double_complex *_tmp2;
  __pyx_t_double_complex *_tmp3;
  int (*forecasting)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *);
  __pyx_t_double_complex (*inversion)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *, __pyx_t_double_complex);
  int (*updating)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *);
  __pyx_t_double_complex (*calculate_loglikelihood)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *, __pyx_t_double_complex);
  int (*prediction)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *);
  int k_endog;
  int k_states;
  int k_posdef;
  int k_endog2;
  int k_states2;
  int k_endogstates;
  int ldwork;
};


/* "statsmodels\tsa\statespace\_statespace.pyx":4046
 * 
 * ## State Space Representation
 * cdef class dStatespace(object):             # <<<<<<<<<<<<<<
 *     """
 *     dStatespace(obs, design, obs_intercept, obs_cov, transition, state_intercept, selection, state_cov)
 */
struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dStatespace {
  PyObject_HEAD
  int nobs;
  int k_endog;
  int k_states;
  int k_posdef;
  __Pyx_memviewslice obs;
  __Pyx_memviewslice obs_intercept;
  __Pyx_memviewslice state_intercept;
  __Pyx_memviewslice initial_state;
  __Pyx_memviewslice initial_state_cov;
  __Pyx_memviewslice design;
  __Pyx_memviewslice obs_cov;
  __Pyx_memviewslice transition;
  __Pyx_memviewslice selection;
  __Pyx_memviewslice state_cov;
  __Pyx_memviewslice selected_state_cov;
  __Pyx_memviewslice missing;
  __Pyx_memviewslice nmissing;
  int time_invariant;
  int initialized;
  __Pyx_memviewslice tmp;
  __pyx_t_5numpy_float64_t *_obs;
  __pyx_t_5numpy_float64_t *_design;
  __pyx_t_5numpy_float64_t *_obs_intercept;
  __pyx_t_5numpy_float64_t *_obs_cov;
  __pyx_t_5numpy_float64_t *_transition;
  __pyx_t_5numpy_float64_t *_state_intercept;
  __pyx_t_5numpy_float64_t *_selection;
  __pyx_t_5numpy_float64_t *_state_cov;
  __pyx_t_5numpy_float64_t *_selected_state_cov;
  __pyx_t_5numpy_float64_t *_initial_state;
  __pyx_t_5numpy_float64_t *_initial_state_cov;
};


/* "statsmodels\tsa\statespace\_statespace.pyx":4840
 * # ## Kalman filter
 * 
 * cdef class dKalmanFilter(object):             # <<<<<<<<<<<<<<
 *     """
 *     dKalmanFilter(model, filter=FILTER_CONVENTIONAL, inversion_method=INVERT_UNIVARIATE | SOLVE_CHOLESKY, stability_method=STABILITY_FORCE_SYMMETRY, tolerance=1e-19)
 */
struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter {
  PyObject_HEAD
  struct __pyx_vtabstruct_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_vtab;
  struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dStatespace *model;
  int t;
  __pyx_t_5numpy_float64_t tolerance;
  int converged;
  int period_converged;
  int time_invariant;
  int filter_method;
  int inversion_method;
  int stability_method;
  int conserve_memory;
  int loglikelihood_burn;
  __Pyx_memviewslice loglikelihood;
  __Pyx_memviewslice filtered_state;
  __Pyx_memviewslice predicted_state;
  __Pyx_memviewslice forecast;
  __Pyx_memviewslice forecast_error;
  __Pyx_memviewslice filtered_state_cov;
  __Pyx_memviewslice predicted_state_cov;
  __Pyx_memviewslice forecast_error_cov;
  __Pyx_memviewslice converged_forecast_error_cov;
  __Pyx_memviewslice converged_filtered_state_cov;
  __Pyx_memviewslice converged_predicted_state_cov;
  __pyx_t_5numpy_float64_t converged_determinant;
  __Pyx_memviewslice selected_obs;
  __Pyx_memviewslice selected_design;
  __Pyx_memviewslice selected_obs_cov;
  __Pyx_memviewslice forecast_error_fac;
  __Pyx_memviewslice forecast_error_ipiv;
  __Pyx_memviewslice forecast_error_work;
  __Pyx_memviewslice tmp0;
  __Pyx_memviewslice tmp1;
  __Pyx_memviewslice tmp3;
  __Pyx_memviewslice tmp2;
  __pyx_t_5numpy_float64_t determinant;
  __pyx_t_5numpy_float64_t *_obs;
  __pyx_t_5numpy_float64_t *_design;
  __pyx_t_5numpy_float64_t *_obs_intercept;
  __pyx_t_5numpy_float64_t *_obs_cov;
  __pyx_t_5numpy_float64_t *_transition;
  __pyx_t_5numpy_float64_t *_state_intercept;
  __pyx_t_5numpy_float64_t *_selection;
  __pyx_t_5numpy_float64_t *_state_cov;
  __pyx_t_5numpy_float64_t *_selected_state_cov;
  __pyx_t_5numpy_float64_t *_initial_state;
  __pyx_t_5numpy_float64_t *_initial_state_cov;
  __pyx_t_5numpy_float64_t *_input_state;
  __pyx_t_5numpy_float64_t *_input_state_cov;
  __pyx_t_5numpy_float64_t *_forecast;
  __pyx_t_5numpy_float64_t *_forecast_error;
  __pyx_t_5numpy_float64_t *_forecast_error_cov;
  __pyx_t_5numpy_float64_t *_filtered_state;
  __pyx_t_5numpy_float64_t *_filtered_state_cov;
  __pyx_t_5numpy_float64_t *_predicted_state;
  __pyx_t_5numpy_float64_t *_predicted_state_cov;
  __pyx_t_5numpy_float64_t *_converged_forecast_error_cov;
  __pyx_t_5numpy_float64_t *_converged_filtered_state_cov;
  __pyx_t_5numpy_float64_t *_converged_predicted_state_cov;
  __pyx_t_5numpy_float64_t *_forecast_error_fac;
  int *_forecast_error_ipiv;
  __pyx_t_5numpy_float64_t *_forecast_error_work;
  __pyx_t_5numpy_float64_t *_tmp0;
  __pyx_t_5numpy_float64_t *_tmp1;
  __pyx_t_5numpy_float64_t *_tmp2;
  __pyx_t_5numpy_float64_t *_tmp3;
  int (*forecasting)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *);
  __pyx_t_5numpy_float64_t (*inversion)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *, __pyx_t_5numpy_float64_t);
  int (*updating)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *);
  __pyx_t_5numpy_float64_t (*calculate_loglikelihood)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *, __pyx_t_5numpy_float64_t);
  int (*prediction)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *);
  int k_endog;
  int k_states;
  int k_posdef;
  int k_endog2;
  int k_states2;
  int k_endogstates;
  int ldwork;
};


/* "statsmodels\tsa\statespace\_statespace.pyx":5979
 * 
 * ## State Space Representation
 * cdef class cStatespace(object):             # <<<<<<<<<<<<<<
 *     """
 *     cStatespace(obs, design, obs_intercept, obs_cov, transition, state_intercept, selection, state_cov)
 */
struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cStatespace {
  PyObject_HEAD
  int nobs;
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/* "statsmodels\tsa\statespace\_statespace.pyx":6777
 * # ## Kalman filter
 * 
 * cdef class cKalmanFilter(object):             # <<<<<<<<<<<<<<
 *     """
 *     cKalmanFilter(model, filter=FILTER_CONVENTIONAL, inversion_method=INVERT_UNIVARIATE | SOLVE_CHOLESKY, stability_method=STABILITY_FORCE_SYMMETRY, tolerance=1e-19)
 */
struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter {
  PyObject_HEAD
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  int k_endog2;
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/* "View.MemoryView":99
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/* "statsmodels\tsa\statespace\_statespace.pyx":970
 * # ## Kalman filter
 * 
 * cdef class sKalmanFilter(object):             # <<<<<<<<<<<<<<
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 *     sKalmanFilter(model, filter=FILTER_CONVENTIONAL, inversion_method=INVERT_UNIVARIATE | SOLVE_CHOLESKY, stability_method=STABILITY_FORCE_SYMMETRY, tolerance=1e-19)
 */

struct __pyx_vtabstruct_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter {
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  PyObject *(*initialize_statespace_object_pointers)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *, int __pyx_skip_dispatch);
  PyObject *(*initialize_filter_object_pointers)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *, int __pyx_skip_dispatch);
  void (*initialize_function_pointers)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *);
  void (*select_state_cov)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *);
  PyObject *(*select_missing)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *, int __pyx_skip_dispatch);
  void (*_select_missing_entire_obs)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *);
  void (*_select_missing_partial_obs)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *);
  void (*post_convergence)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *);
  void (*numerical_stability)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *);
  void (*check_convergence)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *);
  void (*migrate_storage)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *);
};
static struct __pyx_vtabstruct_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_vtabptr_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter;


/* "statsmodels\tsa\statespace\_statespace.pyx":2907
 * # ## Kalman filter
 * 
 * cdef class zKalmanFilter(object):             # <<<<<<<<<<<<<<
 *     """
 *     zKalmanFilter(model, filter=FILTER_CONVENTIONAL, inversion_method=INVERT_UNIVARIATE | SOLVE_CHOLESKY, stability_method=STABILITY_FORCE_SYMMETRY, tolerance=1e-19)
 */

struct __pyx_vtabstruct_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter {
  PyObject *(*set_filter_method)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *, int, int __pyx_skip_dispatch, struct __pyx_opt_args_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_set_filter_method *__pyx_optional_args);
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  PyObject *(*initialize_statespace_object_pointers)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *, int __pyx_skip_dispatch);
  PyObject *(*initialize_filter_object_pointers)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *, int __pyx_skip_dispatch);
  void (*initialize_function_pointers)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *);
  void (*select_state_cov)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *);
  PyObject *(*select_missing)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *, int __pyx_skip_dispatch);
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  void (*_select_missing_partial_obs)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *);
  void (*post_convergence)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *);
  void (*numerical_stability)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *);
  void (*check_convergence)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *);
  void (*migrate_storage)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *);
};
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/* "statsmodels\tsa\statespace\_statespace.pyx":4840
 * # ## Kalman filter
 * 
 * cdef class dKalmanFilter(object):             # <<<<<<<<<<<<<<
 *     """
 *     dKalmanFilter(model, filter=FILTER_CONVENTIONAL, inversion_method=INVERT_UNIVARIATE | SOLVE_CHOLESKY, stability_method=STABILITY_FORCE_SYMMETRY, tolerance=1e-19)
 */

struct __pyx_vtabstruct_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter {
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  PyObject *(*initialize_statespace_object_pointers)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *, int __pyx_skip_dispatch);
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  void (*initialize_function_pointers)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *);
  void (*select_state_cov)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *);
  PyObject *(*select_missing)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *, int __pyx_skip_dispatch);
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  void (*_select_missing_partial_obs)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *);
  void (*post_convergence)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *);
  void (*numerical_stability)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *);
  void (*check_convergence)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *);
  void (*migrate_storage)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *);
};
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/* "statsmodels\tsa\statespace\_statespace.pyx":6777
 * # ## Kalman filter
 * 
 * cdef class cKalmanFilter(object):             # <<<<<<<<<<<<<<
 *     """
 *     cKalmanFilter(model, filter=FILTER_CONVENTIONAL, inversion_method=INVERT_UNIVARIATE | SOLVE_CHOLESKY, stability_method=STABILITY_FORCE_SYMMETRY, tolerance=1e-19)
 */

struct __pyx_vtabstruct_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter {
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  void (*_select_missing_partial_obs)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *);
  void (*post_convergence)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *);
  void (*numerical_stability)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *);
  void (*check_convergence)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *);
  void (*migrate_storage)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *);
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#endif

static PyObject *__Pyx_GetBuiltinName(PyObject *name);

#if CYTHON_COMPILING_IN_CPYTHON
static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw);
#else
#define __Pyx_PyObject_Call(func, arg, kw) PyObject_Call(func, arg, kw)
#endif

static CYTHON_INLINE void __Pyx_ErrRestore(PyObject *type, PyObject *value, PyObject *tb);
static CYTHON_INLINE void __Pyx_ErrFetch(PyObject **type, PyObject **value, PyObject **tb);

static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause);

static void __Pyx_RaiseArgtupleInvalid(const char* func_name, int exact,
    Py_ssize_t num_min, Py_ssize_t num_max, Py_ssize_t num_found);

static void __Pyx_RaiseDoubleKeywordsError(const char* func_name, PyObject* kw_name);

static int __Pyx_ParseOptionalKeywords(PyObject *kwds, PyObject **argnames[], \
    PyObject *kwds2, PyObject *values[], Py_ssize_t num_pos_args, \
    const char* function_name);

static CYTHON_INLINE int  __Pyx_GetBufferAndValidate(Py_buffer* buf, PyObject* obj,
    __Pyx_TypeInfo* dtype, int flags, int nd, int cast, __Pyx_BufFmt_StackElem* stack);
static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info);

#define __Pyx_BUF_MAX_NDIMS %(BUF_MAX_NDIMS)d
#define __Pyx_MEMVIEW_DIRECT   1
#define __Pyx_MEMVIEW_PTR      2
#define __Pyx_MEMVIEW_FULL     4
#define __Pyx_MEMVIEW_CONTIG   8
#define __Pyx_MEMVIEW_STRIDED  16
#define __Pyx_MEMVIEW_FOLLOW   32
#define __Pyx_IS_C_CONTIG 1
#define __Pyx_IS_F_CONTIG 2
static int __Pyx_init_memviewslice(
                struct __pyx_memoryview_obj *memview,
                int ndim,
                __Pyx_memviewslice *memviewslice,
                int memview_is_new_reference);
static CYTHON_INLINE int __pyx_add_acquisition_count_locked(
    __pyx_atomic_int *acquisition_count, PyThread_type_lock lock);
static CYTHON_INLINE int __pyx_sub_acquisition_count_locked(
    __pyx_atomic_int *acquisition_count, PyThread_type_lock lock);
#define __pyx_get_slice_count_pointer(memview) (memview->acquisition_count_aligned_p)
#define __pyx_get_slice_count(memview) (*__pyx_get_slice_count_pointer(memview))
#define __PYX_INC_MEMVIEW(slice, have_gil) __Pyx_INC_MEMVIEW(slice, have_gil, __LINE__)
#define __PYX_XDEC_MEMVIEW(slice, have_gil) __Pyx_XDEC_MEMVIEW(slice, have_gil, __LINE__)
static CYTHON_INLINE void __Pyx_INC_MEMVIEW(__Pyx_memviewslice *, int, int);
static CYTHON_INLINE void __Pyx_XDEC_MEMVIEW(__Pyx_memviewslice *, int, int);

static CYTHON_INLINE PyObject *__Pyx_GetModuleGlobalName(PyObject *name);

#if CYTHON_COMPILING_IN_CPYTHON
static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg);
#endif

static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg);

static PyObject* __Pyx_ImportFrom(PyObject* module, PyObject* name);

#ifndef __PYX_FORCE_INIT_THREADS
  #define __PYX_FORCE_INIT_THREADS 0
#endif

static CYTHON_INLINE void __Pyx_ExceptionSave(PyObject **type, PyObject **value, PyObject **tb);
static void __Pyx_ExceptionReset(PyObject *type, PyObject *value, PyObject *tb);

static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb);

static CYTHON_INLINE int __Pyx_ArgTypeTest(PyObject *obj, PyTypeObject *type, int none_allowed,
    const char *name, int exact);

static CYTHON_INLINE int __Pyx_CheckKeywordStrings(PyObject *kwdict, const char* function_name, int kw_allowed);

#define __Pyx_PyIter_Next(obj) __Pyx_PyIter_Next2(obj, NULL)
static CYTHON_INLINE PyObject *__Pyx_PyIter_Next2(PyObject *, PyObject *);

#if CYTHON_COMPILING_IN_CPYTHON
static CYTHON_INLINE PyObject* __Pyx_PyObject_CallNoArg(PyObject *func);
#else
#define __Pyx_PyObject_CallNoArg(func) __Pyx_PyObject_Call(func, __pyx_empty_tuple, NULL)
#endif

static void __Pyx_WriteUnraisable(const char *name, int clineno,
                                  int lineno, const char *filename,
                                  int full_traceback);

static CYTHON_INLINE long __Pyx_mod_long(long, long); /* proto */

static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname);

#if PY_MAJOR_VERSION >= 3
static PyObject *__Pyx_PyDict_GetItem(PyObject *d, PyObject* key) {
    PyObject *value;
    value = PyDict_GetItemWithError(d, key);
    if (unlikely(!value)) {
        if (!PyErr_Occurred()) {
            PyObject* args = PyTuple_Pack(1, key);
            if (likely(args))
                PyErr_SetObject(PyExc_KeyError, args);
            Py_XDECREF(args);
        }
        return NULL;
    }
    Py_INCREF(value);
    return value;
}
#else
    #define __Pyx_PyDict_GetItem(d, key) PyObject_GetItem(d, key)
#endif

static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected);

static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index);

static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void);

static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type);

#include <string.h>

static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals);

static CYTHON_INLINE int __Pyx_PyUnicode_Equals(PyObject* s1, PyObject* s2, int equals);

#if PY_MAJOR_VERSION >= 3
#define __Pyx_PyString_Equals __Pyx_PyUnicode_Equals
#else
#define __Pyx_PyString_Equals __Pyx_PyBytes_Equals
#endif

static CYTHON_INLINE Py_ssize_t __Pyx_div_Py_ssize_t(Py_ssize_t, Py_ssize_t); /* proto */

#define UNARY_NEG_WOULD_OVERFLOW(x)            (((x) < 0) & ((unsigned long)(x) == 0-(unsigned long)(x)))

static CYTHON_UNUSED int __pyx_array_getbuffer(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /*proto*/
static PyObject *get_memview(PyObject *__pyx_v_self); /*proto*/
static CYTHON_INLINE PyObject *__Pyx_GetAttr(PyObject *, PyObject *);

static CYTHON_INLINE PyObject* __Pyx_decode_c_string(
         const char* cstring, Py_ssize_t start, Py_ssize_t stop,
         const char* encoding, const char* errors,
         PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors));

static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb);

#define __Pyx_GetItemInt(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck) \
    (__Pyx_fits_Py_ssize_t(i, type, is_signed) ? \
    __Pyx_GetItemInt_Fast(o, (Py_ssize_t)i, is_list, wraparound, boundscheck) : \
    (is_list ? (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL) : \
               __Pyx_GetItemInt_Generic(o, to_py_func(i))))
#define __Pyx_GetItemInt_List(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck) \
    (__Pyx_fits_Py_ssize_t(i, type, is_signed) ? \
    __Pyx_GetItemInt_List_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) : \
    (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL))
static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i,
                                                              int wraparound, int boundscheck);
#define __Pyx_GetItemInt_Tuple(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck) \
    (__Pyx_fits_Py_ssize_t(i, type, is_signed) ? \
    __Pyx_GetItemInt_Tuple_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) : \
    (PyErr_SetString(PyExc_IndexError, "tuple index out of range"), (PyObject*)NULL))
static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i,
                                                              int wraparound, int boundscheck);
static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j);
static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i,
                                                     int is_list, int wraparound, int boundscheck);

static CYTHON_UNUSED int __pyx_memoryview_getbuffer(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /*proto*/
static PyObject *__pyx_memoryview_transpose(PyObject *__pyx_v_self); /*proto*/
static PyObject *__pyx_memoryview__get__base(PyObject *__pyx_v_self); /*proto*/
static PyObject *__pyx_memoryview_get_shape(PyObject *__pyx_v_self); /*proto*/
#if CYTHON_COMPILING_IN_CPYTHON
static CYTHON_INLINE int __Pyx_ListComp_Append(PyObject* list, PyObject* x) {
    PyListObject* L = (PyListObject*) list;
    Py_ssize_t len = Py_SIZE(list);
    if (likely(L->allocated > len)) {
        Py_INCREF(x);
        PyList_SET_ITEM(list, len, x);
        Py_SIZE(list) = len+1;
        return 0;
    }
    return PyList_Append(list, x);
}
#else
#define __Pyx_ListComp_Append(L,x) PyList_Append(L,x)
#endif

static PyObject *__pyx_memoryview_get_strides(PyObject *__pyx_v_self); /*proto*/
static PyObject *__pyx_memoryview_get_suboffsets(PyObject *__pyx_v_self); /*proto*/
static PyObject *__pyx_memoryview_get_ndim(PyObject *__pyx_v_self); /*proto*/
static PyObject *__pyx_memoryview_get_itemsize(PyObject *__pyx_v_self); /*proto*/
static PyObject *__pyx_memoryview_get_nbytes(PyObject *__pyx_v_self); /*proto*/
static PyObject *__pyx_memoryview_get_size(PyObject *__pyx_v_self); /*proto*/
static CYTHON_INLINE int __Pyx_PyList_Extend(PyObject* L, PyObject* v) {
#if CYTHON_COMPILING_IN_CPYTHON
    PyObject* none = _PyList_Extend((PyListObject*)L, v);
    if (unlikely(!none))
        return -1;
    Py_DECREF(none);
    return 0;
#else
    return PyList_SetSlice(L, PY_SSIZE_T_MAX, PY_SSIZE_T_MAX, v);
#endif
}

#if CYTHON_COMPILING_IN_CPYTHON
static CYTHON_INLINE int __Pyx_PyList_Append(PyObject* list, PyObject* x) {
    PyListObject* L = (PyListObject*) list;
    Py_ssize_t len = Py_SIZE(list);
    if (likely(L->allocated > len) & likely(len > (L->allocated >> 1))) {
        Py_INCREF(x);
        PyList_SET_ITEM(list, len, x);
        Py_SIZE(list) = len+1;
        return 0;
    }
    return PyList_Append(list, x);
}
#else
#define __Pyx_PyList_Append(L,x) PyList_Append(L,x)
#endif

static CYTHON_INLINE long __Pyx_div_long(long, long); /* proto */

static PyObject *__pyx_memoryviewslice__get__base(PyObject *__pyx_v_self); /*proto*/
static int __Pyx_SetVtable(PyObject *dict, void *vtable);

typedef struct {
    int code_line;
    PyCodeObject* code_object;
} __Pyx_CodeObjectCacheEntry;
struct __Pyx_CodeObjectCache {
    int count;
    int max_count;
    __Pyx_CodeObjectCacheEntry* entries;
};
static struct __Pyx_CodeObjectCache __pyx_code_cache = {0,0,NULL};
static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line);
static PyCodeObject *__pyx_find_code_object(int code_line);
static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object);

static void __Pyx_AddTraceback(const char *funcname, int c_line,
                               int py_line, const char *filename);

typedef struct {
  Py_ssize_t shape, strides, suboffsets;
} __Pyx_Buf_DimInfo;
typedef struct {
  size_t refcount;
  Py_buffer pybuffer;
} __Pyx_Buffer;
typedef struct {
  __Pyx_Buffer *rcbuffer;
  char *data;
  __Pyx_Buf_DimInfo diminfo[8];
} __Pyx_LocalBuf_ND;

#if PY_MAJOR_VERSION < 3
    static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags);
    static void __Pyx_ReleaseBuffer(Py_buffer *view);
#else
    #define __Pyx_GetBuffer PyObject_GetBuffer
    #define __Pyx_ReleaseBuffer PyBuffer_Release
#endif


static Py_ssize_t __Pyx_zeros[] = {0, 0, 0, 0, 0, 0, 0, 0};
static Py_ssize_t __Pyx_minusones[] = {-1, -1, -1, -1, -1, -1, -1, -1};

static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level);

static int __pyx_typeinfo_cmp(__Pyx_TypeInfo *a, __Pyx_TypeInfo *b);

static int __Pyx_ValidateAndInit_memviewslice(
                int *axes_specs,
                int c_or_f_flag,
                int buf_flags,
                int ndim,
                __Pyx_TypeInfo *dtype,
                __Pyx_BufFmt_StackElem stack[],
                __Pyx_memviewslice *memviewslice,
                PyObject *original_obj);

static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dcd__nn___pyx_t_5numpy_float32_t(PyObject *);

static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dcd_d__nn___pyx_t_5numpy_float32_t(PyObject *);

static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds_nn___pyx_t_5numpy_float32_t(PyObject *);

static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *);

static CYTHON_INLINE unsigned int __Pyx_PyInt_As_unsigned_int(PyObject *);

static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dcd____pyx_t_double_complex(PyObject *);

static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dcd_d____pyx_t_double_complex(PyObject *);

static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds___pyx_t_double_complex(PyObject *);

static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dcd__nn___pyx_t_5numpy_float64_t(PyObject *);

static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dcd_d__nn___pyx_t_5numpy_float64_t(PyObject *);

static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds_nn___pyx_t_5numpy_float64_t(PyObject *);

static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dcd____pyx_t_float_complex(PyObject *);

static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dcd_d____pyx_t_float_complex(PyObject *);

static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds___pyx_t_float_complex(PyObject *);

static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value);

static PyObject *__pyx_memview_get_nn___pyx_t_5numpy_float32_t(const char *itemp);
static int __pyx_memview_set_nn___pyx_t_5numpy_float32_t(const char *itemp, PyObject *obj);

static PyObject *__pyx_memview_get_int(const char *itemp);
static int __pyx_memview_set_int(const char *itemp, PyObject *obj);

static CYTHON_INLINE long __Pyx_pow_long(long, long); /* proto */

static CYTHON_INLINE PyObject* __Pyx_PyInt_From_unsigned_int(unsigned int value);

static __Pyx_memviewslice
__pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs,
                                 const char *mode, int ndim,
                                 size_t sizeof_dtype, int contig_flag,
                                 int dtype_is_object);

#define __pyx_memoryview_copy_slice_d_dc_nn___pyx_t_5numpy_float32_t_c(slice) \
        __pyx_memoryview_copy_new_contig(&slice, "c", 2,            \
                                         sizeof(__pyx_t_5numpy_float32_t), (PyBUF_C_CONTIGUOUS | PyBUF_FORMAT | PyBUF_WRITABLE), \
                                         0)

#define __pyx_memoryview_copy_slice_dcd__nn___pyx_t_5numpy_float32_t_f(slice) \
        __pyx_memoryview_copy_new_contig(&slice, "fortran", 2,            \
                                         sizeof(__pyx_t_5numpy_float32_t), (PyBUF_F_CONTIGUOUS | PyBUF_FORMAT | PyBUF_WRITABLE), \
                                         0)

static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value);

#if CYTHON_CCOMPLEX
  #ifdef __cplusplus
    #define __Pyx_CREAL(z) ((z).real())
    #define __Pyx_CIMAG(z) ((z).imag())
  #else
    #define __Pyx_CREAL(z) (__real__(z))
    #define __Pyx_CIMAG(z) (__imag__(z))
  #endif
#else
    #define __Pyx_CREAL(z) ((z).real)
    #define __Pyx_CIMAG(z) ((z).imag)
#endif
#if (defined(_WIN32) || defined(__clang__)) && defined(__cplusplus) && CYTHON_CCOMPLEX
    #define __Pyx_SET_CREAL(z,x) ((z).real(x))
    #define __Pyx_SET_CIMAG(z,y) ((z).imag(y))
#else
    #define __Pyx_SET_CREAL(z,x) __Pyx_CREAL(z) = (x)
    #define __Pyx_SET_CIMAG(z,y) __Pyx_CIMAG(z) = (y)
#endif

#define __pyx_PyComplex_FromComplex(z) \
        PyComplex_FromDoubles((double)__Pyx_CREAL(z), \
                              (double)__Pyx_CIMAG(z))

static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double, double);

static __pyx_t_double_complex __Pyx_PyComplex_As___pyx_t_double_complex(PyObject*);

static PyObject *__pyx_memview_get___pyx_t_double_complex(const char *itemp);
static int __pyx_memview_set___pyx_t_double_complex(const char *itemp, PyObject *obj);

#if CYTHON_CCOMPLEX
    #define __Pyx_c_eq(a, b)   ((a)==(b))
    #define __Pyx_c_sum(a, b)  ((a)+(b))
    #define __Pyx_c_diff(a, b) ((a)-(b))
    #define __Pyx_c_prod(a, b) ((a)*(b))
    #define __Pyx_c_quot(a, b) ((a)/(b))
    #define __Pyx_c_neg(a)     (-(a))
  #ifdef __cplusplus
    #define __Pyx_c_is_zero(z) ((z)==(double)0)
    #define __Pyx_c_conj(z)    (::std::conj(z))
    #if 1
        #define __Pyx_c_abs(z)     (::std::abs(z))
        #define __Pyx_c_pow(a, b)  (::std::pow(a, b))
    #endif
  #else
    #define __Pyx_c_is_zero(z) ((z)==0)
    #define __Pyx_c_conj(z)    (conj(z))
    #if 1
        #define __Pyx_c_abs(z)     (cabs(z))
        #define __Pyx_c_pow(a, b)  (cpow(a, b))
    #endif
 #endif
#else
    static CYTHON_INLINE int __Pyx_c_eq(__pyx_t_double_complex, __pyx_t_double_complex);
    static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum(__pyx_t_double_complex, __pyx_t_double_complex);
    static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff(__pyx_t_double_complex, __pyx_t_double_complex);
    static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod(__pyx_t_double_complex, __pyx_t_double_complex);
    static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot(__pyx_t_double_complex, __pyx_t_double_complex);
    static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg(__pyx_t_double_complex);
    static CYTHON_INLINE int __Pyx_c_is_zero(__pyx_t_double_complex);
    static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj(__pyx_t_double_complex);
    #if 1
        static CYTHON_INLINE double __Pyx_c_abs(__pyx_t_double_complex);
        static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_pow(__pyx_t_double_complex, __pyx_t_double_complex);
    #endif
#endif

#define __pyx_memoryview_copy_slice_d_dc___pyx_t_double_complex_c(slice) \
        __pyx_memoryview_copy_new_contig(&slice, "c", 2,            \
                                         sizeof(__pyx_t_double_complex), (PyBUF_C_CONTIGUOUS | PyBUF_FORMAT | PyBUF_WRITABLE), \
                                         0)

#define __pyx_memoryview_copy_slice_dcd____pyx_t_double_complex_f(slice) \
        __pyx_memoryview_copy_new_contig(&slice, "fortran", 2,            \
                                         sizeof(__pyx_t_double_complex), (PyBUF_F_CONTIGUOUS | PyBUF_FORMAT | PyBUF_WRITABLE), \
                                         0)

static PyObject *__pyx_memview_get_nn___pyx_t_5numpy_float64_t(const char *itemp);
static int __pyx_memview_set_nn___pyx_t_5numpy_float64_t(const char *itemp, PyObject *obj);

#define __pyx_memoryview_copy_slice_d_dc_nn___pyx_t_5numpy_float64_t_c(slice) \
        __pyx_memoryview_copy_new_contig(&slice, "c", 2,            \
                                         sizeof(__pyx_t_5numpy_float64_t), (PyBUF_C_CONTIGUOUS | PyBUF_FORMAT | PyBUF_WRITABLE), \
                                         0)

#define __pyx_memoryview_copy_slice_dcd__nn___pyx_t_5numpy_float64_t_f(slice) \
        __pyx_memoryview_copy_new_contig(&slice, "fortran", 2,            \
                                         sizeof(__pyx_t_5numpy_float64_t), (PyBUF_F_CONTIGUOUS | PyBUF_FORMAT | PyBUF_WRITABLE), \
                                         0)

static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float, float);

static __pyx_t_float_complex __Pyx_PyComplex_As___pyx_t_float_complex(PyObject*);

static PyObject *__pyx_memview_get___pyx_t_float_complex(const char *itemp);
static int __pyx_memview_set___pyx_t_float_complex(const char *itemp, PyObject *obj);

#if CYTHON_CCOMPLEX
    #define __Pyx_c_eqf(a, b)   ((a)==(b))
    #define __Pyx_c_sumf(a, b)  ((a)+(b))
    #define __Pyx_c_difff(a, b) ((a)-(b))
    #define __Pyx_c_prodf(a, b) ((a)*(b))
    #define __Pyx_c_quotf(a, b) ((a)/(b))
    #define __Pyx_c_negf(a)     (-(a))
  #ifdef __cplusplus
    #define __Pyx_c_is_zerof(z) ((z)==(float)0)
    #define __Pyx_c_conjf(z)    (::std::conj(z))
    #if 1
        #define __Pyx_c_absf(z)     (::std::abs(z))
        #define __Pyx_c_powf(a, b)  (::std::pow(a, b))
    #endif
  #else
    #define __Pyx_c_is_zerof(z) ((z)==0)
    #define __Pyx_c_conjf(z)    (conjf(z))
    #if 1
        #define __Pyx_c_absf(z)     (cabsf(z))
        #define __Pyx_c_powf(a, b)  (cpowf(a, b))
    #endif
 #endif
#else
    static CYTHON_INLINE int __Pyx_c_eqf(__pyx_t_float_complex, __pyx_t_float_complex);
    static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sumf(__pyx_t_float_complex, __pyx_t_float_complex);
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static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *);

static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *);

static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dcd__int(PyObject *);

static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds_int(PyObject *);

static int __Pyx_check_binary_version(void);

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static PyObject *__Pyx_ImportModule(const char *name);

static PyTypeObject *__Pyx_ImportType(const char *module_name, const char *class_name, size_t size, int strict);

static int __Pyx_InitStrings(__Pyx_StringTabEntry *t);

static PyObject *__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_set_filter_method(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self, int __pyx_v_filter_method, int __pyx_skip_dispatch, struct __pyx_opt_args_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_set_filter_method *__pyx_optional_args); /* proto*/
static PyObject *__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_seek(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self, unsigned int __pyx_v_t, int __pyx_skip_dispatch, struct __pyx_opt_args_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_seek *__pyx_optional_args); /* proto*/
static PyObject *__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_initialize_statespace_object_pointers(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self, int __pyx_skip_dispatch); /* proto*/
static PyObject *__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_initialize_filter_object_pointers(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self, int __pyx_skip_dispatch); /* proto*/
static void __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_initialize_function_pointers(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto*/
static void __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_select_state_cov(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto*/
static PyObject *__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_select_missing(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self, int __pyx_skip_dispatch); /* proto*/
static void __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter__select_missing_entire_obs(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto*/
static void __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter__select_missing_partial_obs(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto*/
static void __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_post_convergence(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto*/
static void __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_numerical_stability(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto*/
static void __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_check_convergence(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto*/
static void __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_migrate_storage(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto*/
static PyObject *__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_set_filter_method(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self, int __pyx_v_filter_method, int __pyx_skip_dispatch, struct __pyx_opt_args_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_set_filter_method *__pyx_optional_args); /* proto*/
static PyObject *__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_seek(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self, unsigned int __pyx_v_t, int __pyx_skip_dispatch, struct __pyx_opt_args_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_seek *__pyx_optional_args); /* proto*/
static PyObject *__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_initialize_statespace_object_pointers(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self, int __pyx_skip_dispatch); /* proto*/
static PyObject *__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_initialize_filter_object_pointers(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self, int __pyx_skip_dispatch); /* proto*/
static void __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_initialize_function_pointers(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto*/
static void __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_select_state_cov(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto*/
static PyObject *__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_select_missing(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self, int __pyx_skip_dispatch); /* proto*/
static void __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter__select_missing_entire_obs(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto*/
static void __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter__select_missing_partial_obs(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto*/
static void __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_post_convergence(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto*/
static void __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_numerical_stability(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto*/
static void __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_check_convergence(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto*/
static void __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_migrate_storage(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto*/
static PyObject *__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_set_filter_method(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self, int __pyx_v_filter_method, int __pyx_skip_dispatch, struct __pyx_opt_args_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_set_filter_method *__pyx_optional_args); /* proto*/
static PyObject *__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_seek(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self, unsigned int __pyx_v_t, int __pyx_skip_dispatch, struct __pyx_opt_args_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_seek *__pyx_optional_args); /* proto*/
static PyObject *__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_initialize_statespace_object_pointers(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self, int __pyx_skip_dispatch); /* proto*/
static PyObject *__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_initialize_filter_object_pointers(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self, int __pyx_skip_dispatch); /* proto*/
static void __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_initialize_function_pointers(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto*/
static void __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_select_state_cov(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto*/
static PyObject *__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_select_missing(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self, int __pyx_skip_dispatch); /* proto*/
static void __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter__select_missing_entire_obs(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto*/
static void __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter__select_missing_partial_obs(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto*/
static void __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_post_convergence(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto*/
static void __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_numerical_stability(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto*/
static void __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_check_convergence(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto*/
static void __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_migrate_storage(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto*/
static PyObject *__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_set_filter_method(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self, int __pyx_v_filter_method, int __pyx_skip_dispatch, struct __pyx_opt_args_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_set_filter_method *__pyx_optional_args); /* proto*/
static PyObject *__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_seek(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self, unsigned int __pyx_v_t, int __pyx_skip_dispatch, struct __pyx_opt_args_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_seek *__pyx_optional_args); /* proto*/
static PyObject *__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_initialize_statespace_object_pointers(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self, int __pyx_skip_dispatch); /* proto*/
static PyObject *__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_initialize_filter_object_pointers(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self, int __pyx_skip_dispatch); /* proto*/
static void __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_initialize_function_pointers(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto*/
static void __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_select_state_cov(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto*/
static PyObject *__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_select_missing(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self, int __pyx_skip_dispatch); /* proto*/
static void __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter__select_missing_entire_obs(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto*/
static void __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter__select_missing_partial_obs(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto*/
static void __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_post_convergence(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto*/
static void __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_numerical_stability(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto*/
static void __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_check_convergence(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto*/
static void __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_migrate_storage(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto*/
static char *__pyx_memoryview_get_item_pointer(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); /* proto*/
static PyObject *__pyx_memoryview_is_slice(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj); /* proto*/
static PyObject *__pyx_memoryview_setitem_slice_assignment(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_dst, PyObject *__pyx_v_src); /* proto*/
static PyObject *__pyx_memoryview_setitem_slice_assign_scalar(struct __pyx_memoryview_obj *__pyx_v_self, struct __pyx_memoryview_obj *__pyx_v_dst, PyObject *__pyx_v_value); /* proto*/
static PyObject *__pyx_memoryview_setitem_indexed(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index, PyObject *__pyx_v_value); /* proto*/
static PyObject *__pyx_memoryview_convert_item_to_object(struct __pyx_memoryview_obj *__pyx_v_self, char *__pyx_v_itemp); /* proto*/
static PyObject *__pyx_memoryview_assign_item_from_object(struct __pyx_memoryview_obj *__pyx_v_self, char *__pyx_v_itemp, PyObject *__pyx_v_value); /* proto*/
static PyObject *__pyx_memoryviewslice_convert_item_to_object(struct __pyx_memoryviewslice_obj *__pyx_v_self, char *__pyx_v_itemp); /* proto*/
static PyObject *__pyx_memoryviewslice_assign_item_from_object(struct __pyx_memoryviewslice_obj *__pyx_v_self, char *__pyx_v_itemp, PyObject *__pyx_v_value); /* proto*/

/* Module declarations from 'cpython.buffer' */

/* Module declarations from 'cpython.ref' */

/* Module declarations from 'libc.string' */

/* Module declarations from 'libc.stdio' */

/* Module declarations from 'cpython.object' */

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/* Module declarations from 'cpython.type' */
static PyTypeObject *__pyx_ptype_7cpython_4type_type = 0;

/* Module declarations from 'libc.stdlib' */

/* Module declarations from 'numpy' */

/* Module declarations from 'numpy' */
static PyTypeObject *__pyx_ptype_5numpy_dtype = 0;
static PyTypeObject *__pyx_ptype_5numpy_flatiter = 0;
static PyTypeObject *__pyx_ptype_5numpy_broadcast = 0;
static PyTypeObject *__pyx_ptype_5numpy_ndarray = 0;
static PyTypeObject *__pyx_ptype_5numpy_ufunc = 0;
static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *, char *, char *, int *); /*proto*/

/* Module declarations from 'cython.view' */
static struct __pyx_array_obj *__pyx_array_new(PyObject *, Py_ssize_t, char *, char *, char *); /*proto*/

/* Module declarations from 'cython' */

/* Module declarations from 'libc.math' */

/* Module declarations from 'statsmodels.src.blas_lapack' */

/* Module declarations from 'statsmodels.tsa.statespace._statespace' */
static PyTypeObject *__pyx_ptype_11statsmodels_3tsa_10statespace_11_statespace_sStatespace = 0;
static PyTypeObject *__pyx_ptype_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter = 0;
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static PyTypeObject *__pyx_ptype_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter = 0;
static PyTypeObject *__pyx_ptype_11statsmodels_3tsa_10statespace_11_statespace_dStatespace = 0;
static PyTypeObject *__pyx_ptype_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter = 0;
static PyTypeObject *__pyx_ptype_11statsmodels_3tsa_10statespace_11_statespace_cStatespace = 0;
static PyTypeObject *__pyx_ptype_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter = 0;
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static PyTypeObject *__pyx_memoryviewslice_type = 0;
static int __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_FILTER_CONVENTIONAL;
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static int __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_FILTER_AUGMENTED;
static int __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_FILTER_SQUARE_ROOT;
static int __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_FILTER_UNIVARIATE;
static int __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_FILTER_COLLAPSED;
static int __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_FILTER_EXTENDED;
static int __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_FILTER_UNSCENTED;
static int __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_INVERT_UNIVARIATE;
static int __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_SOLVE_LU;
static int __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_INVERT_LU;
static int __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_SOLVE_CHOLESKY;
static int __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_INVERT_CHOLESKY;
static int __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_STABILITY_FORCE_SYMMETRY;
static int __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_MEMORY_STORE_ALL;
static int __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_MEMORY_NO_FORECAST;
static int __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_MEMORY_NO_PREDICTED;
static int __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_MEMORY_NO_FILTERED;
static int __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_MEMORY_NO_LIKELIHOOD;
static int __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_MEMORY_CONSERVE;
static __pyx_t_11statsmodels_3src_11blas_lapack_sgemm_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_sgemm;
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static __pyx_t_11statsmodels_3src_11blas_lapack_saxpy_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_saxpy;
static __pyx_t_11statsmodels_3src_11blas_lapack_sscal_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_sscal;
static __pyx_t_11statsmodels_3src_11blas_lapack_sgetrf_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_sgetrf;
static __pyx_t_11statsmodels_3src_11blas_lapack_sgetri_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_sgetri;
static __pyx_t_11statsmodels_3src_11blas_lapack_sgetrs_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_sgetrs;
static __pyx_t_11statsmodels_3src_11blas_lapack_spotrf_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_spotrf;
static __pyx_t_11statsmodels_3src_11blas_lapack_spotri_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_spotri;
static __pyx_t_11statsmodels_3src_11blas_lapack_spotrs_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_spotrs;
static __pyx_t_11statsmodels_3src_11blas_lapack_strtrs_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_strtrs;
static __pyx_t_11statsmodels_3src_11blas_lapack_zgemm_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zgemm;
static __pyx_t_11statsmodels_3src_11blas_lapack_zgemv_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zgemv;
static __pyx_t_11statsmodels_3src_11blas_lapack_zcopy_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zcopy;
static __pyx_t_11statsmodels_3src_11blas_lapack_zaxpy_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zaxpy;
static __pyx_t_11statsmodels_3src_11blas_lapack_zscal_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zscal;
static __pyx_t_11statsmodels_3src_11blas_lapack_zgetrf_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zgetrf;
static __pyx_t_11statsmodels_3src_11blas_lapack_zgetri_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zgetri;
static __pyx_t_11statsmodels_3src_11blas_lapack_zgetrs_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zgetrs;
static __pyx_t_11statsmodels_3src_11blas_lapack_zpotrf_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zpotrf;
static __pyx_t_11statsmodels_3src_11blas_lapack_zpotri_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zpotri;
static __pyx_t_11statsmodels_3src_11blas_lapack_zpotrs_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zpotrs;
static __pyx_t_11statsmodels_3src_11blas_lapack_ztrtrs_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_ztrtrs;
static __pyx_t_11statsmodels_3src_11blas_lapack_dgemm_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dgemm;
static __pyx_t_11statsmodels_3src_11blas_lapack_dgemv_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dgemv;
static __pyx_t_11statsmodels_3src_11blas_lapack_dcopy_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dcopy;
static __pyx_t_11statsmodels_3src_11blas_lapack_daxpy_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_daxpy;
static __pyx_t_11statsmodels_3src_11blas_lapack_dscal_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dscal;
static __pyx_t_11statsmodels_3src_11blas_lapack_dgetrf_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dgetrf;
static __pyx_t_11statsmodels_3src_11blas_lapack_dgetri_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dgetri;
static __pyx_t_11statsmodels_3src_11blas_lapack_dgetrs_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dgetrs;
static __pyx_t_11statsmodels_3src_11blas_lapack_dpotrf_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dpotrf;
static __pyx_t_11statsmodels_3src_11blas_lapack_dpotri_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dpotri;
static __pyx_t_11statsmodels_3src_11blas_lapack_dpotrs_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dpotrs;
static __pyx_t_11statsmodels_3src_11blas_lapack_dtrtrs_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dtrtrs;
static __pyx_t_11statsmodels_3src_11blas_lapack_cgemm_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_cgemm;
static __pyx_t_11statsmodels_3src_11blas_lapack_cgemv_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_cgemv;
static __pyx_t_11statsmodels_3src_11blas_lapack_ccopy_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_ccopy;
static __pyx_t_11statsmodels_3src_11blas_lapack_caxpy_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_caxpy;
static __pyx_t_11statsmodels_3src_11blas_lapack_cscal_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_cscal;
static __pyx_t_11statsmodels_3src_11blas_lapack_cgetrf_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_cgetrf;
static __pyx_t_11statsmodels_3src_11blas_lapack_cgetri_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_cgetri;
static __pyx_t_11statsmodels_3src_11blas_lapack_cgetrs_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_cgetrs;
static __pyx_t_11statsmodels_3src_11blas_lapack_cpotrf_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_cpotrf;
static __pyx_t_11statsmodels_3src_11blas_lapack_cpotri_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_cpotri;
static __pyx_t_11statsmodels_3src_11blas_lapack_cpotrs_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_cpotrs;
static __pyx_t_11statsmodels_3src_11blas_lapack_ctrtrs_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_ctrtrs;
static __pyx_t_11statsmodels_3src_11blas_lapack_sdot_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_sdot;
static __pyx_t_11statsmodels_3src_11blas_lapack_ddot_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_ddot;
static __pyx_t_11statsmodels_3src_11blas_lapack_cdotu_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_cdot;
static __pyx_t_11statsmodels_3src_11blas_lapack_zdotu_t *__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zdot;
static int __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_FORTRAN;
static PyObject *generic = 0;
static PyObject *strided = 0;
static PyObject *indirect = 0;
static PyObject *contiguous = 0;
static PyObject *indirect_contiguous = 0;
static CYTHON_INLINE __pyx_t_5numpy_float64_t __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_zabs(__pyx_t_double_complex); /*proto*/
static CYTHON_INLINE __pyx_t_double_complex __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_zlog(__pyx_t_double_complex); /*proto*/
static PyObject *__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_validate_matrix_shape(PyObject *, Py_ssize_t *, int, int, struct __pyx_opt_args_11statsmodels_3tsa_10statespace_11_statespace_validate_matrix_shape *__pyx_optional_args); /*proto*/
static PyObject *__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_validate_vector_shape(PyObject *, Py_ssize_t *, int, struct __pyx_opt_args_11statsmodels_3tsa_10statespace_11_statespace_validate_vector_shape *__pyx_optional_args); /*proto*/
static int __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_sselect_state_cov(int, int, __pyx_t_5numpy_float32_t *, __pyx_t_5numpy_float32_t *, __pyx_t_5numpy_float32_t *, __pyx_t_5numpy_float32_t *); /*proto*/
static int __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_sforecast_missing_conventional(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *); /*proto*/
static int __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_supdating_missing_conventional(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *); /*proto*/
static __pyx_t_5numpy_float32_t __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_sinverse_missing_conventional(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *, __pyx_t_5numpy_float32_t); /*proto*/
static __pyx_t_5numpy_float32_t __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_sloglikelihood_missing_conventional(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *, __pyx_t_5numpy_float32_t); /*proto*/
static int __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_sforecast_conventional(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *); /*proto*/
static int __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_supdating_conventional(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *); /*proto*/
static int __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_sprediction_conventional(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *); /*proto*/
static __pyx_t_5numpy_float32_t __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_sloglikelihood_conventional(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *, __pyx_t_5numpy_float32_t); /*proto*/
static __pyx_t_5numpy_float32_t __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_sinverse_univariate(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *, __pyx_t_5numpy_float32_t); /*proto*/
static __pyx_t_5numpy_float32_t __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_sfactorize_cholesky(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *, __pyx_t_5numpy_float32_t); /*proto*/
static __pyx_t_5numpy_float32_t __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_sfactorize_lu(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *, __pyx_t_5numpy_float32_t); /*proto*/
static __pyx_t_5numpy_float32_t __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_sinverse_cholesky(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *, __pyx_t_5numpy_float32_t); /*proto*/
static __pyx_t_5numpy_float32_t __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_sinverse_lu(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *, __pyx_t_5numpy_float32_t); /*proto*/
static __pyx_t_5numpy_float32_t __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_ssolve_cholesky(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *, __pyx_t_5numpy_float32_t); /*proto*/
static __pyx_t_5numpy_float32_t __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_ssolve_lu(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *, __pyx_t_5numpy_float32_t); /*proto*/
static PyObject *__pyx_f_11statsmodels_3tsa_10statespace_11_statespace__scompute_coefficients_from_multivariate_pacf(__Pyx_memviewslice, __Pyx_memviewslice, int, int, int, int __pyx_skip_dispatch); /*proto*/
static PyObject *__pyx_f_11statsmodels_3tsa_10statespace_11_statespace__sconstrain_sv_less_than_one(__Pyx_memviewslice, int, int, int __pyx_skip_dispatch); /*proto*/
static int __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_zselect_state_cov(int, int, __pyx_t_double_complex *, __pyx_t_double_complex *, __pyx_t_double_complex *, __pyx_t_double_complex *); /*proto*/
static int __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_zforecast_missing_conventional(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *); /*proto*/
static int __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_zupdating_missing_conventional(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *); /*proto*/
static __pyx_t_double_complex __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_zinverse_missing_conventional(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *, __pyx_t_double_complex); /*proto*/
static __pyx_t_double_complex __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_zloglikelihood_missing_conventional(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *, __pyx_t_double_complex); /*proto*/
static int __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_zforecast_conventional(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *); /*proto*/
static int __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_zupdating_conventional(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *); /*proto*/
static int __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_zprediction_conventional(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *); /*proto*/
static __pyx_t_double_complex __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_zloglikelihood_conventional(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *, __pyx_t_double_complex); /*proto*/
static __pyx_t_double_complex __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_zinverse_univariate(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *, __pyx_t_double_complex); /*proto*/
static __pyx_t_double_complex __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_zfactorize_cholesky(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *, __pyx_t_double_complex); /*proto*/
static __pyx_t_double_complex __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_zfactorize_lu(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *, __pyx_t_double_complex); /*proto*/
static __pyx_t_double_complex __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_zinverse_cholesky(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *, __pyx_t_double_complex); /*proto*/
static __pyx_t_double_complex __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_zinverse_lu(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *, __pyx_t_double_complex); /*proto*/
static __pyx_t_double_complex __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_zsolve_cholesky(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *, __pyx_t_double_complex); /*proto*/
static __pyx_t_double_complex __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_zsolve_lu(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *, __pyx_t_double_complex); /*proto*/
static PyObject *__pyx_f_11statsmodels_3tsa_10statespace_11_statespace__zcompute_coefficients_from_multivariate_pacf(__Pyx_memviewslice, __Pyx_memviewslice, int, int, int, int __pyx_skip_dispatch); /*proto*/
static PyObject *__pyx_f_11statsmodels_3tsa_10statespace_11_statespace__zconstrain_sv_less_than_one(__Pyx_memviewslice, int, int, int __pyx_skip_dispatch); /*proto*/
static int __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_dselect_state_cov(int, int, __pyx_t_5numpy_float64_t *, __pyx_t_5numpy_float64_t *, __pyx_t_5numpy_float64_t *, __pyx_t_5numpy_float64_t *); /*proto*/
static int __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_dforecast_missing_conventional(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *); /*proto*/
static int __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_dupdating_missing_conventional(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *); /*proto*/
static __pyx_t_5numpy_float64_t __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_dinverse_missing_conventional(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *, __pyx_t_5numpy_float64_t); /*proto*/
static __pyx_t_5numpy_float64_t __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_dloglikelihood_missing_conventional(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *, __pyx_t_5numpy_float64_t); /*proto*/
static int __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_dforecast_conventional(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *); /*proto*/
static int __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_dupdating_conventional(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *); /*proto*/
static int __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_dprediction_conventional(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *); /*proto*/
static __pyx_t_5numpy_float64_t __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_dloglikelihood_conventional(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *, __pyx_t_5numpy_float64_t); /*proto*/
static __pyx_t_5numpy_float64_t __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_dinverse_univariate(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *, __pyx_t_5numpy_float64_t); /*proto*/
static __pyx_t_5numpy_float64_t __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_dfactorize_cholesky(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *, __pyx_t_5numpy_float64_t); /*proto*/
static __pyx_t_5numpy_float64_t __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_dfactorize_lu(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *, __pyx_t_5numpy_float64_t); /*proto*/
static __pyx_t_5numpy_float64_t __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_dinverse_cholesky(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *, __pyx_t_5numpy_float64_t); /*proto*/
static __pyx_t_5numpy_float64_t __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_dinverse_lu(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *, __pyx_t_5numpy_float64_t); /*proto*/
static __pyx_t_5numpy_float64_t __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_dsolve_cholesky(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *, __pyx_t_5numpy_float64_t); /*proto*/
static __pyx_t_5numpy_float64_t __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_dsolve_lu(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *, __pyx_t_5numpy_float64_t); /*proto*/
static PyObject *__pyx_f_11statsmodels_3tsa_10statespace_11_statespace__dcompute_coefficients_from_multivariate_pacf(__Pyx_memviewslice, __Pyx_memviewslice, int, int, int, int __pyx_skip_dispatch); /*proto*/
static PyObject *__pyx_f_11statsmodels_3tsa_10statespace_11_statespace__dconstrain_sv_less_than_one(__Pyx_memviewslice, int, int, int __pyx_skip_dispatch); /*proto*/
static int __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_cselect_state_cov(int, int, __pyx_t_float_complex *, __pyx_t_float_complex *, __pyx_t_float_complex *, __pyx_t_float_complex *); /*proto*/
static int __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_cforecast_missing_conventional(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *); /*proto*/
static int __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_cupdating_missing_conventional(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *); /*proto*/
static __pyx_t_float_complex __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_cinverse_missing_conventional(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *, __pyx_t_float_complex); /*proto*/
static __pyx_t_float_complex __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_cloglikelihood_missing_conventional(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *, __pyx_t_float_complex); /*proto*/
static int __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_cforecast_conventional(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *); /*proto*/
static int __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_cupdating_conventional(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *); /*proto*/
static int __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_cprediction_conventional(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *); /*proto*/
static __pyx_t_float_complex __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_cloglikelihood_conventional(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *, __pyx_t_float_complex); /*proto*/
static __pyx_t_float_complex __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_cinverse_univariate(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *, __pyx_t_float_complex); /*proto*/
static __pyx_t_float_complex __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_cfactorize_cholesky(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *, __pyx_t_float_complex); /*proto*/
static __pyx_t_float_complex __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_cfactorize_lu(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *, __pyx_t_float_complex); /*proto*/
static __pyx_t_float_complex __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_cinverse_cholesky(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *, __pyx_t_float_complex); /*proto*/
static __pyx_t_float_complex __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_cinverse_lu(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *, __pyx_t_float_complex); /*proto*/
static __pyx_t_float_complex __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_csolve_cholesky(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *, __pyx_t_float_complex); /*proto*/
static __pyx_t_float_complex __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_csolve_lu(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *, __pyx_t_float_complex); /*proto*/
static PyObject *__pyx_f_11statsmodels_3tsa_10statespace_11_statespace__ccompute_coefficients_from_multivariate_pacf(__Pyx_memviewslice, __Pyx_memviewslice, int, int, int, int __pyx_skip_dispatch); /*proto*/
static PyObject *__pyx_f_11statsmodels_3tsa_10statespace_11_statespace__cconstrain_sv_less_than_one(__Pyx_memviewslice, int, int, int __pyx_skip_dispatch); /*proto*/
static struct __pyx_array_obj *__pyx_array_new(PyObject *, Py_ssize_t, char *, char *, char *); /*proto*/
static void *__pyx_align_pointer(void *, size_t); /*proto*/
static PyObject *__pyx_memoryview_new(PyObject *, int, int, __Pyx_TypeInfo *); /*proto*/
static CYTHON_INLINE int __pyx_memoryview_check(PyObject *); /*proto*/
static PyObject *_unellipsify(PyObject *, int); /*proto*/
static PyObject *assert_direct_dimensions(Py_ssize_t *, int); /*proto*/
static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_obj *, PyObject *); /*proto*/
static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *, Py_ssize_t, Py_ssize_t, Py_ssize_t, int, int, int *, Py_ssize_t, Py_ssize_t, Py_ssize_t, int, int, int, int); /*proto*/
static char *__pyx_pybuffer_index(Py_buffer *, char *, Py_ssize_t, Py_ssize_t); /*proto*/
static int __pyx_memslice_transpose(__Pyx_memviewslice *); /*proto*/
static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice, int, PyObject *(*)(char *), int (*)(char *, PyObject *), int); /*proto*/
static __Pyx_memviewslice *__pyx_memoryview_get_slice_from_memoryview(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/
static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/
static PyObject *__pyx_memoryview_copy_object(struct __pyx_memoryview_obj *); /*proto*/
static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/
static Py_ssize_t abs_py_ssize_t(Py_ssize_t); /*proto*/
static char __pyx_get_best_slice_order(__Pyx_memviewslice *, int); /*proto*/
static void _copy_strided_to_strided(char *, Py_ssize_t *, char *, Py_ssize_t *, Py_ssize_t *, Py_ssize_t *, int, size_t); /*proto*/
static void copy_strided_to_strided(__Pyx_memviewslice *, __Pyx_memviewslice *, int, size_t); /*proto*/
static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *, int); /*proto*/
static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *, Py_ssize_t *, Py_ssize_t, int, char); /*proto*/
static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *, __Pyx_memviewslice *, char, int); /*proto*/
static int __pyx_memoryview_err_extents(int, Py_ssize_t, Py_ssize_t); /*proto*/
static int __pyx_memoryview_err_dim(PyObject *, char *, int); /*proto*/
static int __pyx_memoryview_err(PyObject *, char *); /*proto*/
static int __pyx_memoryview_copy_contents(__Pyx_memviewslice, __Pyx_memviewslice, int, int, int); /*proto*/
static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *, int, int); /*proto*/
static void __pyx_memoryview_refcount_copying(__Pyx_memviewslice *, int, int, int); /*proto*/
static void __pyx_memoryview_refcount_objects_in_slice_with_gil(char *, Py_ssize_t *, Py_ssize_t *, int, int); /*proto*/
static void __pyx_memoryview_refcount_objects_in_slice(char *, Py_ssize_t *, Py_ssize_t *, int, int); /*proto*/
static void __pyx_memoryview_slice_assign_scalar(__Pyx_memviewslice *, int, size_t, void *, int); /*proto*/
static void __pyx_memoryview__slice_assign_scalar(char *, Py_ssize_t *, Py_ssize_t *, int, size_t, void *); /*proto*/
static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_5numpy_float32_t = { "float32_t", NULL, sizeof(__pyx_t_5numpy_float32_t), { 0 }, 0, 'R', 0, 0 };
static __Pyx_TypeInfo __Pyx_TypeInfo___pyx_t_double_complex = { "double complex", NULL, sizeof(__pyx_t_double_complex), { 0 }, 0, 'C', 0, 0 };
static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_5numpy_float64_t = { "float64_t", NULL, sizeof(__pyx_t_5numpy_float64_t), { 0 }, 0, 'R', 0, 0 };
static __Pyx_TypeInfo __Pyx_TypeInfo___pyx_t_float_complex = { "float complex", NULL, sizeof(__pyx_t_float_complex), { 0 }, 0, 'C', 0, 0 };
static __Pyx_TypeInfo __Pyx_TypeInfo_int = { "int", NULL, sizeof(int), { 0 }, 0, IS_UNSIGNED(int) ? 'U' : 'I', IS_UNSIGNED(int), 0 };
#define __Pyx_MODULE_NAME "statsmodels.tsa.statespace._statespace"
int __pyx_module_is_main_statsmodels__tsa__statespace___statespace = 0;

/* Implementation of 'statsmodels.tsa.statespace._statespace' */
static PyObject *__pyx_builtin_ValueError;
static PyObject *__pyx_builtin_range;
static PyObject *__pyx_builtin_NotImplementedError;
static PyObject *__pyx_builtin_IndexError;
static PyObject *__pyx_builtin_StopIteration;
static PyObject *__pyx_builtin_RuntimeError;
static PyObject *__pyx_builtin_MemoryError;
static PyObject *__pyx_builtin_enumerate;
static PyObject *__pyx_builtin_Ellipsis;
static PyObject *__pyx_builtin_TypeError;
static PyObject *__pyx_builtin_id;
static int __pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace___init__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sStatespace *__pyx_v_self, __Pyx_memviewslice __pyx_v_obs, __Pyx_memviewslice __pyx_v_design, __Pyx_memviewslice __pyx_v_obs_intercept, __Pyx_memviewslice __pyx_v_obs_cov, __Pyx_memviewslice __pyx_v_transition, __Pyx_memviewslice __pyx_v_state_intercept, __Pyx_memviewslice __pyx_v_selection, __Pyx_memviewslice __pyx_v_state_cov); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_2initialize_known(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sStatespace *__pyx_v_self, __Pyx_memviewslice __pyx_v_initial_state, __Pyx_memviewslice __pyx_v_initial_state_cov); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_4initialize_approximate_diffuse(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sStatespace *__pyx_v_self, PyObject *__pyx_v_variance); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_6initialize_stationary(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sStatespace *__pyx_v_self, PyObject *__pyx_v_complex_step); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_4nobs___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_7k_endog___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_8k_states___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_8k_posdef___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_3obs___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_13obs_intercept___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_15state_intercept___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_13initial_state___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_17initial_state_cov___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_6design___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_7obs_cov___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_10transition___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_9selection___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_9state_cov___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_18selected_state_cov___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_7missing___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_8nmissing___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_14time_invariant___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_11initialized___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sStatespace *__pyx_v_self); /* proto */
static int __pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter___init__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self, struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sStatespace *__pyx_v_model, int __pyx_v_filter_method, int __pyx_v_inversion_method, int __pyx_v_stability_method, int __pyx_v_conserve_memory, __pyx_t_5numpy_float64_t __pyx_v_tolerance, int __pyx_v_loglikelihood_burn); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_2set_filter_method(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self, int __pyx_v_filter_method, int __pyx_v_force_reset); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_4seek(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self, unsigned int __pyx_v_t, int __pyx_v_reset_convergence); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_6__iter__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_8__call__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_10__next__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_12initialize_statespace_object_pointers(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_14initialize_filter_object_pointers(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_16select_missing(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_5model___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_1t___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_9tolerance___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static int __pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_9tolerance_2__set__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_9converged___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_16period_converged___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_14time_invariant___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_13filter_method___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static int __pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_13filter_method_2__set__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_16inversion_method___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static int __pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_16inversion_method_2__set__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_16stability_method___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static int __pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_16stability_method_2__set__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_15conserve_memory___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_18loglikelihood_burn___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_13loglikelihood___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_14filtered_state___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_15predicted_state___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_8forecast___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_14forecast_error___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_18filtered_state_cov___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_19predicted_state_cov___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_18forecast_error_cov___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_28converged_forecast_error_cov___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_28converged_filtered_state_cov___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_29converged_predicted_state_cov___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_21converged_determinant___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_12selected_obs___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_15selected_design___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_16selected_obs_cov___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_18forecast_error_fac___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_19forecast_error_ipiv___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_19forecast_error_work___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_4tmp0___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_4tmp1___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_4tmp3___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_4tmp2___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_11determinant___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_7k_endog___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_8k_states___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_8k_posdef___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_8k_endog2___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_9k_states2___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_13k_endogstates___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_6ldwork___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace__scompute_coefficients_from_multivariate_pacf(CYTHON_UNUSED PyObject *__pyx_self, __Pyx_memviewslice __pyx_v_partial_autocorrelations, __Pyx_memviewslice __pyx_v_error_variance, int __pyx_v_transform_variance, int __pyx_v_order, int __pyx_v_k_endog); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_2_sconstrain_sv_less_than_one(CYTHON_UNUSED PyObject *__pyx_self, __Pyx_memviewslice __pyx_v_unconstrained, int __pyx_v_order, int __pyx_v_k_endog); /* proto */
static int __pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace___init__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zStatespace *__pyx_v_self, __Pyx_memviewslice __pyx_v_obs, __Pyx_memviewslice __pyx_v_design, __Pyx_memviewslice __pyx_v_obs_intercept, __Pyx_memviewslice __pyx_v_obs_cov, __Pyx_memviewslice __pyx_v_transition, __Pyx_memviewslice __pyx_v_state_intercept, __Pyx_memviewslice __pyx_v_selection, __Pyx_memviewslice __pyx_v_state_cov); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_2initialize_known(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zStatespace *__pyx_v_self, __Pyx_memviewslice __pyx_v_initial_state, __Pyx_memviewslice __pyx_v_initial_state_cov); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_4initialize_approximate_diffuse(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zStatespace *__pyx_v_self, PyObject *__pyx_v_variance); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_6initialize_stationary(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zStatespace *__pyx_v_self, PyObject *__pyx_v_complex_step); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_4nobs___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_7k_endog___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_8k_states___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_8k_posdef___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_3obs___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_13obs_intercept___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_15state_intercept___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_13initial_state___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_17initial_state_cov___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_6design___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_7obs_cov___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_10transition___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_9selection___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_9state_cov___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_18selected_state_cov___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_7missing___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_8nmissing___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_14time_invariant___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_11initialized___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zStatespace *__pyx_v_self); /* proto */
static int __pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter___init__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self, struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zStatespace *__pyx_v_model, int __pyx_v_filter_method, int __pyx_v_inversion_method, int __pyx_v_stability_method, int __pyx_v_conserve_memory, __pyx_t_5numpy_float64_t __pyx_v_tolerance, int __pyx_v_loglikelihood_burn); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_2set_filter_method(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self, int __pyx_v_filter_method, int __pyx_v_force_reset); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_4seek(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self, unsigned int __pyx_v_t, int __pyx_v_reset_convergence); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_6__iter__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_8__call__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_10__next__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_12initialize_statespace_object_pointers(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_14initialize_filter_object_pointers(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_16select_missing(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_5model___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_1t___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_9tolerance___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static int __pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_9tolerance_2__set__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_9converged___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_16period_converged___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_14time_invariant___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_13filter_method___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static int __pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_13filter_method_2__set__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_16inversion_method___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static int __pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_16inversion_method_2__set__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_16stability_method___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static int __pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_16stability_method_2__set__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_15conserve_memory___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_18loglikelihood_burn___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_13loglikelihood___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_14filtered_state___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_15predicted_state___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_8forecast___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_14forecast_error___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_18filtered_state_cov___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_19predicted_state_cov___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_18forecast_error_cov___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_28converged_forecast_error_cov___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_28converged_filtered_state_cov___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_29converged_predicted_state_cov___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_21converged_determinant___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_12selected_obs___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_15selected_design___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_16selected_obs_cov___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_18forecast_error_fac___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_19forecast_error_ipiv___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_19forecast_error_work___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_4tmp0___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_4tmp1___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_4tmp3___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_4tmp2___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_11determinant___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_7k_endog___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_8k_states___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_8k_posdef___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_8k_endog2___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_9k_states2___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_13k_endogstates___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_6ldwork___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_4_zcompute_coefficients_from_multivariate_pacf(CYTHON_UNUSED PyObject *__pyx_self, __Pyx_memviewslice __pyx_v_partial_autocorrelations, __Pyx_memviewslice __pyx_v_error_variance, int __pyx_v_transform_variance, int __pyx_v_order, int __pyx_v_k_endog); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_6_zconstrain_sv_less_than_one(CYTHON_UNUSED PyObject *__pyx_self, __Pyx_memviewslice __pyx_v_unconstrained, int __pyx_v_order, int __pyx_v_k_endog); /* proto */
static int __pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace___init__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dStatespace *__pyx_v_self, __Pyx_memviewslice __pyx_v_obs, __Pyx_memviewslice __pyx_v_design, __Pyx_memviewslice __pyx_v_obs_intercept, __Pyx_memviewslice __pyx_v_obs_cov, __Pyx_memviewslice __pyx_v_transition, __Pyx_memviewslice __pyx_v_state_intercept, __Pyx_memviewslice __pyx_v_selection, __Pyx_memviewslice __pyx_v_state_cov); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_2initialize_known(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dStatespace *__pyx_v_self, __Pyx_memviewslice __pyx_v_initial_state, __Pyx_memviewslice __pyx_v_initial_state_cov); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_4initialize_approximate_diffuse(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dStatespace *__pyx_v_self, PyObject *__pyx_v_variance); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_6initialize_stationary(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dStatespace *__pyx_v_self, PyObject *__pyx_v_complex_step); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_4nobs___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_7k_endog___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_8k_states___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_8k_posdef___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_3obs___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_13obs_intercept___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_15state_intercept___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_13initial_state___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_17initial_state_cov___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_6design___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_7obs_cov___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_10transition___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_9selection___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_9state_cov___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_18selected_state_cov___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_7missing___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_8nmissing___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_14time_invariant___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_11initialized___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dStatespace *__pyx_v_self); /* proto */
static int __pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter___init__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self, struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dStatespace *__pyx_v_model, int __pyx_v_filter_method, int __pyx_v_inversion_method, int __pyx_v_stability_method, int __pyx_v_conserve_memory, __pyx_t_5numpy_float64_t __pyx_v_tolerance, int __pyx_v_loglikelihood_burn); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_2set_filter_method(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self, int __pyx_v_filter_method, int __pyx_v_force_reset); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_4seek(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self, unsigned int __pyx_v_t, int __pyx_v_reset_convergence); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_6__iter__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_8__call__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_10__next__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_12initialize_statespace_object_pointers(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_14initialize_filter_object_pointers(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_16select_missing(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_5model___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_1t___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_9tolerance___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static int __pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_9tolerance_2__set__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_9converged___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_16period_converged___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_14time_invariant___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_13filter_method___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static int __pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_13filter_method_2__set__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_16inversion_method___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static int __pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_16inversion_method_2__set__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_16stability_method___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static int __pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_16stability_method_2__set__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_15conserve_memory___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_18loglikelihood_burn___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_13loglikelihood___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_14filtered_state___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_15predicted_state___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_8forecast___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_14forecast_error___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_18filtered_state_cov___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_19predicted_state_cov___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_18forecast_error_cov___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_28converged_forecast_error_cov___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_28converged_filtered_state_cov___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_29converged_predicted_state_cov___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_21converged_determinant___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_12selected_obs___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_15selected_design___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_16selected_obs_cov___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_18forecast_error_fac___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_19forecast_error_ipiv___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_19forecast_error_work___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_4tmp0___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_4tmp1___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_4tmp3___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_4tmp2___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_11determinant___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_7k_endog___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_8k_states___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_8k_posdef___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_8k_endog2___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_9k_states2___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_13k_endogstates___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_6ldwork___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_8_dcompute_coefficients_from_multivariate_pacf(CYTHON_UNUSED PyObject *__pyx_self, __Pyx_memviewslice __pyx_v_partial_autocorrelations, __Pyx_memviewslice __pyx_v_error_variance, int __pyx_v_transform_variance, int __pyx_v_order, int __pyx_v_k_endog); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_10_dconstrain_sv_less_than_one(CYTHON_UNUSED PyObject *__pyx_self, __Pyx_memviewslice __pyx_v_unconstrained, int __pyx_v_order, int __pyx_v_k_endog); /* proto */
static int __pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace___init__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cStatespace *__pyx_v_self, __Pyx_memviewslice __pyx_v_obs, __Pyx_memviewslice __pyx_v_design, __Pyx_memviewslice __pyx_v_obs_intercept, __Pyx_memviewslice __pyx_v_obs_cov, __Pyx_memviewslice __pyx_v_transition, __Pyx_memviewslice __pyx_v_state_intercept, __Pyx_memviewslice __pyx_v_selection, __Pyx_memviewslice __pyx_v_state_cov); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_2initialize_known(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cStatespace *__pyx_v_self, __Pyx_memviewslice __pyx_v_initial_state, __Pyx_memviewslice __pyx_v_initial_state_cov); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_4initialize_approximate_diffuse(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cStatespace *__pyx_v_self, PyObject *__pyx_v_variance); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_6initialize_stationary(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cStatespace *__pyx_v_self, PyObject *__pyx_v_complex_step); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_4nobs___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_7k_endog___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_8k_states___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_8k_posdef___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_3obs___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_13obs_intercept___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_15state_intercept___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_13initial_state___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_17initial_state_cov___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_6design___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_7obs_cov___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_10transition___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_9selection___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_9state_cov___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_18selected_state_cov___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_7missing___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_8nmissing___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_14time_invariant___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cStatespace *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_11initialized___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cStatespace *__pyx_v_self); /* proto */
static int __pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter___init__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self, struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cStatespace *__pyx_v_model, int __pyx_v_filter_method, int __pyx_v_inversion_method, int __pyx_v_stability_method, int __pyx_v_conserve_memory, __pyx_t_5numpy_float64_t __pyx_v_tolerance, int __pyx_v_loglikelihood_burn); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_2set_filter_method(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self, int __pyx_v_filter_method, int __pyx_v_force_reset); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_4seek(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self, unsigned int __pyx_v_t, int __pyx_v_reset_convergence); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_6__iter__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_8__call__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_10__next__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_12initialize_statespace_object_pointers(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_14initialize_filter_object_pointers(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_16select_missing(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_5model___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_1t___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_9tolerance___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static int __pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_9tolerance_2__set__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_9converged___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_16period_converged___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_14time_invariant___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_13filter_method___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static int __pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_13filter_method_2__set__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_16inversion_method___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static int __pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_16inversion_method_2__set__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_16stability_method___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static int __pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_16stability_method_2__set__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_15conserve_memory___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_18loglikelihood_burn___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_13loglikelihood___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_14filtered_state___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_15predicted_state___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_8forecast___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_14forecast_error___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_18filtered_state_cov___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_19predicted_state_cov___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_18forecast_error_cov___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_28converged_forecast_error_cov___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_28converged_filtered_state_cov___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_29converged_predicted_state_cov___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_21converged_determinant___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_12selected_obs___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_15selected_design___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_16selected_obs_cov___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_18forecast_error_fac___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_19forecast_error_ipiv___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_19forecast_error_work___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_4tmp0___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_4tmp1___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_4tmp3___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_4tmp2___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_11determinant___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_7k_endog___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_8k_states___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_8k_posdef___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_8k_endog2___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_9k_states2___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_13k_endogstates___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_6ldwork___get__(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_12_ccompute_coefficients_from_multivariate_pacf(CYTHON_UNUSED PyObject *__pyx_self, __Pyx_memviewslice __pyx_v_partial_autocorrelations, __Pyx_memviewslice __pyx_v_error_variance, int __pyx_v_transform_variance, int __pyx_v_order, int __pyx_v_k_endog); /* proto */
static PyObject *__pyx_pf_11statsmodels_3tsa_10statespace_11_statespace_14_cconstrain_sv_less_than_one(CYTHON_UNUSED PyObject *__pyx_self, __Pyx_memviewslice __pyx_v_unconstrained, int __pyx_v_order, int __pyx_v_k_endog); /* proto */
static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */
static void __pyx_pf_5numpy_7ndarray_2__releasebuffer__(PyArrayObject *__pyx_v_self, Py_buffer *__pyx_v_info); /* proto */
static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array___cinit__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_shape, Py_ssize_t __pyx_v_itemsize, PyObject *__pyx_v_format, PyObject *__pyx_v_mode, int __pyx_v_allocate_buffer); /* proto */
static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array_2__getbuffer__(struct __pyx_array_obj *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */
static void __pyx_array___pyx_pf_15View_dot_MemoryView_5array_4__dealloc__(struct __pyx_array_obj *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_15View_dot_MemoryView_5array_7memview___get__(struct __pyx_array_obj *__pyx_v_self); /* proto */
static PyObject *__pyx_array___pyx_pf_15View_dot_MemoryView_5array_6__getattr__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_attr); /* proto */
static PyObject *__pyx_array___pyx_pf_15View_dot_MemoryView_5array_8__getitem__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_item); /* proto */
static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array_10__setitem__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_item, PyObject *__pyx_v_value); /* proto */
static int __pyx_MemviewEnum___pyx_pf_15View_dot_MemoryView_4Enum___init__(struct __pyx_MemviewEnum_obj *__pyx_v_self, PyObject *__pyx_v_name); /* proto */
static PyObject *__pyx_MemviewEnum___pyx_pf_15View_dot_MemoryView_4Enum_2__repr__(struct __pyx_MemviewEnum_obj *__pyx_v_self); /* proto */
static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview___cinit__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj, int __pyx_v_flags, int __pyx_v_dtype_is_object); /* proto */
static void __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_2__dealloc__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_4__getitem__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); /* proto */
static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_6__setitem__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index, PyObject *__pyx_v_value); /* proto */
static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_8__getbuffer__(struct __pyx_memoryview_obj *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */
static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_1T___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_4base___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_5shape___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_7strides___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_10suboffsets___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_4ndim___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_8itemsize___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_6nbytes___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_4size___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
static Py_ssize_t __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_10__len__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_12__repr__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_14__str__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_16is_c_contig(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_18is_f_contig(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_20copy(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_22copy_fortran(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
static void __pyx_memoryviewslice___pyx_pf_15View_dot_MemoryView_16_memoryviewslice___dealloc__(struct __pyx_memoryviewslice_obj *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_15View_dot_MemoryView_16_memoryviewslice_4base___get__(struct __pyx_memoryviewslice_obj *__pyx_v_self); /* proto */
static PyObject *__pyx_tp_new_11statsmodels_3tsa_10statespace_11_statespace_sStatespace(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
static PyObject *__pyx_tp_new_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
static PyObject *__pyx_tp_new_11statsmodels_3tsa_10statespace_11_statespace_zStatespace(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
static PyObject *__pyx_tp_new_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
static PyObject *__pyx_tp_new_11statsmodels_3tsa_10statespace_11_statespace_dStatespace(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
static PyObject *__pyx_tp_new_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
static PyObject *__pyx_tp_new_11statsmodels_3tsa_10statespace_11_statespace_cStatespace(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
static PyObject *__pyx_tp_new_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
static PyObject *__pyx_tp_new_array(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
static PyObject *__pyx_tp_new_Enum(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
static PyObject *__pyx_tp_new_memoryview(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
static PyObject *__pyx_tp_new__memoryviewslice(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
static char __pyx_k_B[] = "B";
static char __pyx_k_F[] = "F";
static char __pyx_k_H[] = "H";
static char __pyx_k_I[] = "I";
static char __pyx_k_L[] = "L";
static char __pyx_k_N[] = "N";
static char __pyx_k_O[] = "O";
static char __pyx_k_Q[] = "Q";
static char __pyx_k_R[] = "R";
static char __pyx_k_T[] = "T";
static char __pyx_k_U[] = "U";
static char __pyx_k_b[] = "b";
static char __pyx_k_c[] = "c";
static char __pyx_k_d[] = "d";
static char __pyx_k_f[] = "f";
static char __pyx_k_g[] = "g";
static char __pyx_k_h[] = "h";
static char __pyx_k_i[] = "i";
static char __pyx_k_l[] = "l";
static char __pyx_k_q[] = "q";
static char __pyx_k_t[] = "t";
static char __pyx_k_Zd[] = "Zd";
static char __pyx_k_Zf[] = "Zf";
static char __pyx_k_Zg[] = "Zg";
static char __pyx_k_id[] = "id";
static char __pyx_k_np[] = "np";
static char __pyx_k_eye[] = "eye";
static char __pyx_k_obj[] = "obj";
static char __pyx_k_obs[] = "obs";
static char __pyx_k_sum[] = "sum";
static char __pyx_k_axis[] = "axis";
static char __pyx_k_base[] = "base";
static char __pyx_k_blas[] = "blas";
static char __pyx_k_ddot[] = "ddot";
static char __pyx_k_main[] = "__main__";
static char __pyx_k_mode[] = "mode";
static char __pyx_k_name[] = "name";
static char __pyx_k_ndim[] = "ndim";
static char __pyx_k_pack[] = "pack";
static char __pyx_k_sdot[] = "sdot";
static char __pyx_k_seek[] = "seek";
static char __pyx_k_size[] = "size";
static char __pyx_k_step[] = "step";
static char __pyx_k_stop[] = "stop";
static char __pyx_k_test[] = "__test__";
static char __pyx_k_array[] = "array";
static char __pyx_k_caxpy[] = "caxpy";
static char __pyx_k_ccopy[] = "ccopy";
static char __pyx_k_cdotu[] = "cdotu";
static char __pyx_k_cgbsv[] = "cgbsv";
static char __pyx_k_cgemm[] = "cgemm";
static char __pyx_k_cgemv[] = "cgemv";
static char __pyx_k_cgerc[] = "cgerc";
static char __pyx_k_class[] = "__class__";
static char __pyx_k_cscal[] = "cscal";
static char __pyx_k_ctrmm[] = "ctrmm";
static char __pyx_k_daxpy[] = "daxpy";
static char __pyx_k_dcopy[] = "dcopy";
static char __pyx_k_dgemm[] = "dgemm";
static char __pyx_k_dgemv[] = "dgemv";
static char __pyx_k_dscal[] = "dscal";
static char __pyx_k_dtrmm[] = "dtrmm";
static char __pyx_k_dtype[] = "dtype";
static char __pyx_k_error[] = "error";
static char __pyx_k_fblas[] = "fblas";
static char __pyx_k_flags[] = "flags";
static char __pyx_k_int32[] = "int32";
static char __pyx_k_isnan[] = "isnan";
static char __pyx_k_model[] = "model";
static char __pyx_k_numpy[] = "numpy";
static char __pyx_k_order[] = "order";
static char __pyx_k_range[] = "range";
static char __pyx_k_saxpy[] = "saxpy";
static char __pyx_k_scopy[] = "scopy";
static char __pyx_k_sgemm[] = "sgemm";
static char __pyx_k_sgemv[] = "sgemv";
static char __pyx_k_shape[] = "shape";
static char __pyx_k_sscal[] = "sscal";
static char __pyx_k_start[] = "start";
static char __pyx_k_strmm[] = "strmm";
static char __pyx_k_tools[] = "tools";
static char __pyx_k_zaxpy[] = "zaxpy";
static char __pyx_k_zcopy[] = "zcopy";
static char __pyx_k_zdotu[] = "zdotu";
static char __pyx_k_zgemm[] = "zgemm";
static char __pyx_k_zgemv[] = "zgemv";
static char __pyx_k_zscal[] = "zscal";
static char __pyx_k_ztrmm[] = "ztrmm";
static char __pyx_k_cgetrf[] = "cgetrf";
static char __pyx_k_cgetri[] = "cgetri";
static char __pyx_k_cgetrs[] = "cgetrs";
static char __pyx_k_cpotrf[] = "cpotrf";
static char __pyx_k_cpotri[] = "cpotri";
static char __pyx_k_cpotrs[] = "cpotrs";
static char __pyx_k_ctrtrs[] = "ctrtrs";
static char __pyx_k_design[] = "design";
static char __pyx_k_dgetrf[] = "dgetrf";
static char __pyx_k_dgetri[] = "dgetri";
static char __pyx_k_dgetrs[] = "dgetrs";
static char __pyx_k_dpotrf[] = "dpotrf";
static char __pyx_k_dpotri[] = "dpotri";
static char __pyx_k_dpotrs[] = "dpotrs";
static char __pyx_k_dtrtrs[] = "dtrtrs";
static char __pyx_k_format[] = "format";
static char __pyx_k_import[] = "__import__";
static char __pyx_k_lapack[] = "lapack";
static char __pyx_k_linalg[] = "linalg";
static char __pyx_k_name_2[] = "__name__";
static char __pyx_k_sgetrf[] = "sgetrf";
static char __pyx_k_sgetri[] = "sgetri";
static char __pyx_k_sgetrs[] = "sgetrs";
static char __pyx_k_spotrf[] = "spotrf";
static char __pyx_k_spotri[] = "spotri";
static char __pyx_k_spotrs[] = "spotrs";
static char __pyx_k_strtrs[] = "strtrs";
static char __pyx_k_struct[] = "struct";
static char __pyx_k_unpack[] = "unpack";
static char __pyx_k_zgetrf[] = "zgetrf";
static char __pyx_k_zgetri[] = "zgetri";
static char __pyx_k_zgetrs[] = "zgetrs";
static char __pyx_k_zpotrf[] = "zpotrf";
static char __pyx_k_zpotri[] = "zpotri";
static char __pyx_k_zpotrs[] = "zpotrs";
static char __pyx_k_ztrtrs[] = "ztrtrs";
static char __pyx_k_flapack[] = "flapack";
static char __pyx_k_float32[] = "float32";
static char __pyx_k_fortran[] = "fortran";
static char __pyx_k_k_endog[] = "k_endog";
static char __pyx_k_memview[] = "memview";
static char __pyx_k_obs_cov[] = "obs_cov";
static char __pyx_k_Ellipsis[] = "Ellipsis";
static char __pyx_k_cpointer[] = "_cpointer";
static char __pyx_k_itemsize[] = "itemsize";
static char __pyx_k_variance[] = "variance";
static char __pyx_k_warnings[] = "warnings";
static char __pyx_k_TypeError[] = "TypeError";
static char __pyx_k_complex64[] = "complex64";
static char __pyx_k_enumerate[] = "enumerate";
static char __pyx_k_selection[] = "selection";
static char __pyx_k_state_cov[] = "state_cov";
static char __pyx_k_tolerance[] = "tolerance";
static char __pyx_k_IndexError[] = "IndexError";
static char __pyx_k_ValueError[] = "ValueError";
static char __pyx_k_pyx_vtable[] = "__pyx_vtable__";
static char __pyx_k_transition[] = "transition";
static char __pyx_k_LinAlgError[] = "LinAlgError";
static char __pyx_k_MemoryError[] = "MemoryError";
static char __pyx_k_force_reset[] = "force_reset";
static char __pyx_k_RuntimeError[] = "RuntimeError";
static char __pyx_k_complex_step[] = "complex_step";
static char __pyx_k_inital_state[] = "inital state";
static char __pyx_k_scipy_linalg[] = "scipy.linalg";
static char __pyx_k_StopIteration[] = "StopIteration";
static char __pyx_k_filter_method[] = "filter_method";
static char __pyx_k_initial_state[] = "initial_state";
static char __pyx_k_obs_intercept[] = "obs_intercept";
static char __pyx_k_pyx_getbuffer[] = "__pyx_getbuffer";
static char __pyx_k_unconstrained[] = "unconstrained";
static char __pyx_k_asfortranarray[] = "asfortranarray";
static char __pyx_k_error_variance[] = "error_variance";
static char __pyx_k_select_missing[] = "select_missing";
static char __pyx_k_allocate_buffer[] = "allocate_buffer";
static char __pyx_k_conserve_memory[] = "conserve_memory";
static char __pyx_k_dtype_is_object[] = "dtype_is_object";
static char __pyx_k_state_intercept[] = "state_intercept";
static char __pyx_k_inversion_method[] = "inversion_method";
static char __pyx_k_stability_method[] = "stability_method";
static char __pyx_k_initial_state_cov[] = "initial_state_cov";
static char __pyx_k_reset_convergence[] = "reset_convergence";
static char __pyx_k_scipy_linalg_blas[] = "scipy.linalg.blas";
static char __pyx_k_set_filter_method[] = "set_filter_method";
static char __pyx_k_state_intercept_2[] = "state intercept";
static char __pyx_k_loglikelihood_burn[] = "loglikelihood_burn";
static char __pyx_k_strided_and_direct[] = "<strided and direct>";
static char __pyx_k_transform_variance[] = "transform_variance";
static char __pyx_k_NotImplementedError[] = "NotImplementedError";
static char __pyx_k_scipy_linalg_lapack[] = "scipy.linalg.lapack";
static char __pyx_k_strided_and_indirect[] = "<strided and indirect>";
static char __pyx_k_contiguous_and_direct[] = "<contiguous and direct>";
static char __pyx_k_observation_intercept[] = "observation intercept";
static char __pyx_k_MemoryView_of_r_object[] = "<MemoryView of %r object>";
static char __pyx_k_MemoryView_of_r_at_0x_x[] = "<MemoryView of %r at 0x%x>";
static char __pyx_k_contiguous_and_indirect[] = "<contiguous and indirect>";
static char __pyx_k_solve_discrete_lyapunov[] = "solve_discrete_lyapunov";
static char __pyx_k_state_covariance_matrix[] = "state covariance matrix";
static char __pyx_k_Cannot_index_with_type_s[] = "Cannot index with type '%s'";
static char __pyx_k_Invalid_filtering_method[] = "Invalid filtering method";
static char __pyx_k_Invalid_inversion_method[] = "Invalid inversion method";
static char __pyx_k_getbuffer_obj_view_flags[] = "getbuffer(obj, view, flags)";
static char __pyx_k_initial_state_covariance[] = "initial state covariance";
static char __pyx_k_partial_autocorrelations[] = "partial_autocorrelations";
static char __pyx_k_Dimension_d_is_not_direct[] = "Dimension %d is not direct";
static char __pyx_k_Invalid_shape_in_axis_d_d[] = "Invalid shape in axis %d: %d.";
static char __pyx_k_Index_out_of_bounds_axis_d[] = "Index out of bounds (axis %d)";
static char __pyx_k_Step_may_not_be_zero_axis_d[] = "Step may not be zero (axis %d)";
static char __pyx_k_itemsize_0_for_cython_array[] = "itemsize <= 0 for cython.array";
static char __pyx_k_ndarray_is_not_C_contiguous[] = "ndarray is not C contiguous";
static char __pyx_k_observation_covariance_matrix[] = "observation covariance matrix";
static char __pyx_k_unable_to_allocate_array_data[] = "unable to allocate array data.";
static char __pyx_k_Observation_index_out_of_range[] = "Observation index out of range";
static char __pyx_k_State_Space_Models_Author_Chad[] = "\nState Space Models\n\nAuthor: Chad Fulton  \nLicense: Simplified-BSD\n";
static char __pyx_k_strided_and_direct_or_indirect[] = "<strided and direct or indirect>";
static char __pyx_k_Illegal_value_in_forecast_error[] = "Illegal value in forecast error covariance matrix encountered at period %d";
static char __pyx_k_unknown_dtype_code_in_numpy_pxd[] = "unknown dtype code in numpy.pxd (%d)";
static char __pyx_k_All_dimensions_preceding_dimensi[] = "All dimensions preceding dimension %d must be indexed and not sliced";
static char __pyx_k_Buffer_view_does_not_expose_stri[] = "Buffer view does not expose strides";
static char __pyx_k_Can_only_create_a_buffer_that_is[] = "Can only create a buffer that is contiguous in memory.";
static char __pyx_k_Cannot_transpose_memoryview_with[] = "Cannot transpose memoryview with indirect dimensions";
static char __pyx_k_Empty_shape_tuple_for_cython_arr[] = "Empty shape tuple for cython.array";
static char __pyx_k_Format_string_allocated_too_shor[] = "Format string allocated too short, see comment in numpy.pxd";
static char __pyx_k_Indirect_dimensions_not_supporte[] = "Indirect dimensions not supported";
static char __pyx_k_Invalid_mode_expected_c_or_fortr[] = "Invalid mode, expected 'c' or 'fortran', got %s";
static char __pyx_k_Invalid_shape_for_s_matrix_requi[] = "Invalid shape for %s matrix: requires %d rows, got %d";
static char __pyx_k_Invalid_shape_for_s_vector_requi[] = "Invalid shape for %s vector: requires %d rows, got %d";
static char __pyx_k_Invalid_time_varying_dimension_f[] = "Invalid time-varying dimension for %s matrix: requires 1 or %d, got %d";
static char __pyx_k_Non_native_byte_order_not_suppor[] = "Non-native byte order not supported";
static char __pyx_k_Non_positive_definite_forecast_e[] = "Non-positive-definite forecast error covariance matrix encountered at period %d";
static char __pyx_k_Only_the_conventional_Kalman_fil[] = "Only the conventional Kalman filter is currently implemented";
static char __pyx_k_Out_of_bounds_on_buffer_access_a[] = "Out of bounds on buffer access (axis %d)";
static char __pyx_k_Singular_forecast_error_covarian[] = "Singular forecast error covariance matrix encountered at period %d";
static char __pyx_k_Statespace_model_not_initialized[] = "Statespace model not initialized.";
static char __pyx_k_Unable_to_convert_item_to_object[] = "Unable to convert item to object";
static char __pyx_k_got_differing_extents_in_dimensi[] = "got differing extents in dimension %d (got %d and %d)";
static char __pyx_k_initialize_filter_object_pointer[] = "initialize_filter_object_pointers";
static char __pyx_k_initialize_statespace_object_poi[] = "initialize_statespace_object_pointers";
static char __pyx_k_ndarray_is_not_Fortran_contiguou[] = "ndarray is not Fortran contiguous";
static char __pyx_k_unable_to_allocate_shape_and_str[] = "unable to allocate shape and strides.";
static char __pyx_k_Format_string_allocated_too_shor_2[] = "Format string allocated too short.";
static char __pyx_k_Invalid_shape_for_s_matrix_requi_2[] = "Invalid shape for %s matrix: requires %d columns,got %d";
static char __pyx_k_Invalid_time_varying_dimension_f_2[] = "Invalid time-varying dimension for %s vector: requires 1 or %d got %d";
static PyObject *__pyx_kp_s_Buffer_view_does_not_expose_stri;
static PyObject *__pyx_kp_s_Can_only_create_a_buffer_that_is;
static PyObject *__pyx_kp_s_Cannot_index_with_type_s;
static PyObject *__pyx_n_s_Ellipsis;
static PyObject *__pyx_kp_s_Empty_shape_tuple_for_cython_arr;
static PyObject *__pyx_n_s_F;
static PyObject *__pyx_kp_u_Format_string_allocated_too_shor;
static PyObject *__pyx_kp_u_Format_string_allocated_too_shor_2;
static PyObject *__pyx_kp_s_Illegal_value_in_forecast_error;
static PyObject *__pyx_n_s_IndexError;
static PyObject *__pyx_kp_s_Indirect_dimensions_not_supporte;
static PyObject *__pyx_kp_s_Invalid_filtering_method;
static PyObject *__pyx_kp_s_Invalid_inversion_method;
static PyObject *__pyx_kp_s_Invalid_mode_expected_c_or_fortr;
static PyObject *__pyx_kp_s_Invalid_shape_for_s_matrix_requi;
static PyObject *__pyx_kp_s_Invalid_shape_for_s_matrix_requi_2;
static PyObject *__pyx_kp_s_Invalid_shape_for_s_vector_requi;
static PyObject *__pyx_kp_s_Invalid_shape_in_axis_d_d;
static PyObject *__pyx_kp_s_Invalid_time_varying_dimension_f;
static PyObject *__pyx_kp_s_Invalid_time_varying_dimension_f_2;
static PyObject *__pyx_n_s_LinAlgError;
static PyObject *__pyx_n_s_MemoryError;
static PyObject *__pyx_kp_s_MemoryView_of_r_at_0x_x;
static PyObject *__pyx_kp_s_MemoryView_of_r_object;
static PyObject *__pyx_kp_u_Non_native_byte_order_not_suppor;
static PyObject *__pyx_kp_s_Non_positive_definite_forecast_e;
static PyObject *__pyx_n_s_NotImplementedError;
static PyObject *__pyx_n_b_O;
static PyObject *__pyx_kp_s_Observation_index_out_of_range;
static PyObject *__pyx_kp_s_Only_the_conventional_Kalman_fil;
static PyObject *__pyx_kp_s_Out_of_bounds_on_buffer_access_a;
static PyObject *__pyx_n_s_RuntimeError;
static PyObject *__pyx_kp_s_Singular_forecast_error_covarian;
static PyObject *__pyx_kp_s_Statespace_model_not_initialized;
static PyObject *__pyx_n_s_StopIteration;
static PyObject *__pyx_n_s_T;
static PyObject *__pyx_n_s_TypeError;
static PyObject *__pyx_kp_s_Unable_to_convert_item_to_object;
static PyObject *__pyx_n_s_ValueError;
static PyObject *__pyx_n_s_allocate_buffer;
static PyObject *__pyx_n_s_array;
static PyObject *__pyx_n_s_asfortranarray;
static PyObject *__pyx_n_s_axis;
static PyObject *__pyx_n_s_base;
static PyObject *__pyx_n_s_blas;
static PyObject *__pyx_n_s_c;
static PyObject *__pyx_n_u_c;
static PyObject *__pyx_n_s_caxpy;
static PyObject *__pyx_n_s_ccopy;
static PyObject *__pyx_n_s_cdotu;
static PyObject *__pyx_n_s_cgbsv;
static PyObject *__pyx_n_s_cgemm;
static PyObject *__pyx_n_s_cgemv;
static PyObject *__pyx_n_s_cgerc;
static PyObject *__pyx_n_s_cgetrf;
static PyObject *__pyx_n_s_cgetri;
static PyObject *__pyx_n_s_cgetrs;
static PyObject *__pyx_n_s_class;
static PyObject *__pyx_n_s_complex64;
static PyObject *__pyx_n_s_complex_step;
static PyObject *__pyx_n_s_conserve_memory;
static PyObject *__pyx_kp_s_contiguous_and_direct;
static PyObject *__pyx_kp_s_contiguous_and_indirect;
static PyObject *__pyx_n_s_cpointer;
static PyObject *__pyx_n_s_cpotrf;
static PyObject *__pyx_n_s_cpotri;
static PyObject *__pyx_n_s_cpotrs;
static PyObject *__pyx_n_s_cscal;
static PyObject *__pyx_n_s_ctrmm;
static PyObject *__pyx_n_s_ctrtrs;
static PyObject *__pyx_n_s_daxpy;
static PyObject *__pyx_n_s_dcopy;
static PyObject *__pyx_n_s_ddot;
static PyObject *__pyx_n_s_design;
static PyObject *__pyx_n_s_dgemm;
static PyObject *__pyx_n_s_dgemv;
static PyObject *__pyx_n_s_dgetrf;
static PyObject *__pyx_n_s_dgetri;
static PyObject *__pyx_n_s_dgetrs;
static PyObject *__pyx_n_s_dpotrf;
static PyObject *__pyx_n_s_dpotri;
static PyObject *__pyx_n_s_dpotrs;
static PyObject *__pyx_n_s_dscal;
static PyObject *__pyx_n_s_dtrmm;
static PyObject *__pyx_n_s_dtrtrs;
static PyObject *__pyx_n_s_dtype;
static PyObject *__pyx_n_s_dtype_is_object;
static PyObject *__pyx_n_s_enumerate;
static PyObject *__pyx_n_s_error;
static PyObject *__pyx_n_s_error_variance;
static PyObject *__pyx_n_s_eye;
static PyObject *__pyx_n_s_fblas;
static PyObject *__pyx_n_s_filter_method;
static PyObject *__pyx_n_s_flags;
static PyObject *__pyx_n_s_flapack;
static PyObject *__pyx_n_s_float32;
static PyObject *__pyx_n_s_force_reset;
static PyObject *__pyx_n_s_format;
static PyObject *__pyx_n_s_fortran;
static PyObject *__pyx_n_u_fortran;
static PyObject *__pyx_kp_s_got_differing_extents_in_dimensi;
static PyObject *__pyx_n_s_id;
static PyObject *__pyx_n_s_import;
static PyObject *__pyx_kp_s_inital_state;
static PyObject *__pyx_n_s_initial_state;
static PyObject *__pyx_n_s_initial_state_cov;
static PyObject *__pyx_kp_s_initial_state_covariance;
static PyObject *__pyx_n_s_initialize_filter_object_pointer;
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 *         np.float32_t beta = 0.0             # <<<<<<<<<<<<<<
 *         np.float32_t gamma = -1.0
 * 
 */
  __pyx_v_beta = 0.0;

  /* "statsmodels\tsa\statespace\_statespace.pyx":541
 *         np.float32_t alpha = 1.0
 *         np.float32_t beta = 0.0
 *         np.float32_t gamma = -1.0             # <<<<<<<<<<<<<<
 * 
 *     # #### Forecast for time t
 */
  __pyx_v_gamma = -1.0;

  /* "statsmodels\tsa\statespace\_statespace.pyx":550
 * 
 *     # $\\# = d_t$
 *     scopy(&kfilter.k_endog, kfilter._obs_intercept, &inc, kfilter._forecast, &inc)             # <<<<<<<<<<<<<<
 *     # `forecast` $= 1.0 * Z_t a_t + 1.0 * \\#$
 *     # $(p \times 1) = (p \times m) (m \times 1) + (p \times 1)$
 */
  __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_scopy((&__pyx_v_kfilter->k_endog), __pyx_v_kfilter->_obs_intercept, (&__pyx_v_inc), __pyx_v_kfilter->_forecast, (&__pyx_v_inc));

  /* "statsmodels\tsa\statespace\_statespace.pyx":553
 *     # `forecast` $= 1.0 * Z_t a_t + 1.0 * \\#$
 *     # $(p \times 1) = (p \times m) (m \times 1) + (p \times 1)$
 *     sgemv("N", &kfilter.k_endog, &kfilter.k_states,             # <<<<<<<<<<<<<<
 *           &alpha, kfilter._design, &kfilter.k_endog,
 *                   kfilter._input_state, &inc,
 */
  __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_sgemv(__pyx_k_N, (&__pyx_v_kfilter->k_endog), (&__pyx_v_kfilter->k_states), (&__pyx_v_alpha), __pyx_v_kfilter->_design, (&__pyx_v_kfilter->k_endog), __pyx_v_kfilter->_input_state, (&__pyx_v_inc), (&__pyx_v_alpha), __pyx_v_kfilter->_forecast, (&__pyx_v_inc));

  /* "statsmodels\tsa\statespace\_statespace.pyx":562
 * 
 *     # $\\# = y_t$
 *     scopy(&kfilter.k_endog, kfilter._obs, &inc, kfilter._forecast_error, &inc)             # <<<<<<<<<<<<<<
 *     # $v_t = -1.0 * $ `forecast` $ + \\#$
 *     # $(p \times 1) = (p \times 1) + (p \times 1)$
 */
  __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_scopy((&__pyx_v_kfilter->k_endog), __pyx_v_kfilter->_obs, (&__pyx_v_inc), __pyx_v_kfilter->_forecast_error, (&__pyx_v_inc));

  /* "statsmodels\tsa\statespace\_statespace.pyx":565
 *     # $v_t = -1.0 * $ `forecast` $ + \\#$
 *     # $(p \times 1) = (p \times 1) + (p \times 1)$
 *     saxpy(&kfilter.k_endog, &gamma, kfilter._forecast, &inc, kfilter._forecast_error, &inc)             # <<<<<<<<<<<<<<
 * 
 *     # *Intermediate calculation* (used just below and then once more)
 */
  __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_saxpy((&__pyx_v_kfilter->k_endog), (&__pyx_v_gamma), __pyx_v_kfilter->_forecast, (&__pyx_v_inc), __pyx_v_kfilter->_forecast_error, (&__pyx_v_inc));

  /* "statsmodels\tsa\statespace\_statespace.pyx":571
 *     # $\\#_1 = P_t Z_t'$
 *     # $(m \times p) = (m \times m) (p \times m)'$
 *     sgemm("N", "T", &kfilter.k_states, &kfilter.k_endog, &kfilter.k_states,             # <<<<<<<<<<<<<<
 *           &alpha, kfilter._input_state_cov, &kfilter.k_states,
 *                   kfilter._design, &kfilter.k_endog,
 */
  __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_sgemm(__pyx_k_N, __pyx_k_T, (&__pyx_v_kfilter->k_states), (&__pyx_v_kfilter->k_endog), (&__pyx_v_kfilter->k_states), (&__pyx_v_alpha), __pyx_v_kfilter->_input_state_cov, (&__pyx_v_kfilter->k_states), __pyx_v_kfilter->_design, (&__pyx_v_kfilter->k_endog), (&__pyx_v_beta), __pyx_v_kfilter->_tmp1, (&__pyx_v_kfilter->k_states));

  /* "statsmodels\tsa\statespace\_statespace.pyx":581
 *     # *Note*: this and does nothing at all to `forecast_error_cov` if
 *     # converged == True
 *     if not kfilter.converged:             # <<<<<<<<<<<<<<
 *         # $\\# = H_t$
 *         scopy(&kfilter.k_endog2, kfilter._obs_cov, &inc, kfilter._forecast_error_cov, &inc)
 */
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    /* "statsmodels\tsa\statespace\_statespace.pyx":583
 *     if not kfilter.converged:
 *         # $\\# = H_t$
 *         scopy(&kfilter.k_endog2, kfilter._obs_cov, &inc, kfilter._forecast_error_cov, &inc)             # <<<<<<<<<<<<<<
 * 
 *         # $F_t = 1.0 * Z_t \\#_1 + 1.0 * \\#$
 */
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    /* "statsmodels\tsa\statespace\_statespace.pyx":586
 * 
 *         # $F_t = 1.0 * Z_t \\#_1 + 1.0 * \\#$
 *         sgemm("N", "N", &kfilter.k_endog, &kfilter.k_endog, &kfilter.k_states,             # <<<<<<<<<<<<<<
 *               &alpha, kfilter._design, &kfilter.k_endog,
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 */
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 *               &alpha, kfilter._forecast_error_cov, &kfilter.k_endog)
 * 
 *     return 0             # <<<<<<<<<<<<<<
 * 
 * cdef int supdating_conventional(sKalmanFilter kfilter):
 */
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  /* "statsmodels\tsa\statespace\_statespace.pyx":534
 * # See Durbin and Koopman (2012) Chapter 4
 * 
 * cdef int sforecast_conventional(sKalmanFilter kfilter):             # <<<<<<<<<<<<<<
 * 
 *     # Constants
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/* "statsmodels\tsa\statespace\_statespace.pyx":593
 *     return 0
 * 
 * cdef int supdating_conventional(sKalmanFilter kfilter):             # <<<<<<<<<<<<<<
 *     # Constants
 *     cdef:
 */

static int __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_supdating_conventional(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_kfilter) {
  int __pyx_v_inc;
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  __pyx_t_5numpy_float32_t __pyx_v_gamma;
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 *         np.float32_t alpha = 1.0
 *         np.float32_t beta = 0.0
 */
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  /* "statsmodels\tsa\statespace\_statespace.pyx":597
 *     cdef:
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 *         np.float32_t alpha = 1.0             # <<<<<<<<<<<<<<
 *         np.float32_t beta = 0.0
 *         np.float32_t gamma = -1.0
 */
  __pyx_v_alpha = 1.0;

  /* "statsmodels\tsa\statespace\_statespace.pyx":598
 *         int inc = 1
 *         np.float32_t alpha = 1.0
 *         np.float32_t beta = 0.0             # <<<<<<<<<<<<<<
 *         np.float32_t gamma = -1.0
 * 
 */
  __pyx_v_beta = 0.0;

  /* "statsmodels\tsa\statespace\_statespace.pyx":599
 *         np.float32_t alpha = 1.0
 *         np.float32_t beta = 0.0
 *         np.float32_t gamma = -1.0             # <<<<<<<<<<<<<<
 * 
 *     # #### Filtered state for time t
 */
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  /* "statsmodels\tsa\statespace\_statespace.pyx":604
 *     # $a_{t|t} = a_t + P_t Z_t' F_t^{-1} v_t$
 *     # $a_{t|t} = 1.0 * \\#_1 \\#_2 + 1.0 a_t$
 *     scopy(&kfilter.k_states, kfilter._input_state, &inc, kfilter._filtered_state, &inc)             # <<<<<<<<<<<<<<
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 */
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  /* "statsmodels\tsa\statespace\_statespace.pyx":605
 *     # $a_{t|t} = 1.0 * \\#_1 \\#_2 + 1.0 a_t$
 *     scopy(&kfilter.k_states, kfilter._input_state, &inc, kfilter._filtered_state, &inc)
 *     sgemv("N", &kfilter.k_states, &kfilter.k_endog,             # <<<<<<<<<<<<<<
 *           &alpha, kfilter._tmp1, &kfilter.k_states,
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 */
  __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_sgemv(__pyx_k_N, (&__pyx_v_kfilter->k_states), (&__pyx_v_kfilter->k_endog), (&__pyx_v_alpha), __pyx_v_kfilter->_tmp1, (&__pyx_v_kfilter->k_states), __pyx_v_kfilter->_tmp2, (&__pyx_v_inc), (&__pyx_v_alpha), __pyx_v_kfilter->_filtered_state, (&__pyx_v_inc));

  /* "statsmodels\tsa\statespace\_statespace.pyx":616
 *     # *Note*: this and does nothing at all to `filtered_state_cov` if
 *     # converged == True
 *     if not kfilter.converged:             # <<<<<<<<<<<<<<
 *         scopy(&kfilter.k_states2, kfilter._input_state_cov, &inc, kfilter._filtered_state_cov, &inc)
 * 
 */
  __pyx_t_1 = ((!(__pyx_v_kfilter->converged != 0)) != 0);
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    /* "statsmodels\tsa\statespace\_statespace.pyx":617
 *     # converged == True
 *     if not kfilter.converged:
 *         scopy(&kfilter.k_states2, kfilter._input_state_cov, &inc, kfilter._filtered_state_cov, &inc)             # <<<<<<<<<<<<<<
 * 
 *         # `tmp0` array used here, dimension $(m \times m)$
 */
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_scopy((&__pyx_v_kfilter->k_states2), __pyx_v_kfilter->_input_state_cov, (&__pyx_v_inc), __pyx_v_kfilter->_filtered_state_cov, (&__pyx_v_inc));

    /* "statsmodels\tsa\statespace\_statespace.pyx":622
 *         # $\\#_0 = 1.0 * \\#_1 \\#_3$
 *         # $(m \times m) = (m \times p) (p \times m)$
 *         sgemm("N", "N", &kfilter.k_states, &kfilter.k_states, &kfilter.k_endog,             # <<<<<<<<<<<<<<
 *               &alpha, kfilter._tmp1, &kfilter.k_states,
 *                       kfilter._tmp3, &kfilter.k_endog,
 */
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_sgemm(__pyx_k_N, __pyx_k_N, (&__pyx_v_kfilter->k_states), (&__pyx_v_kfilter->k_states), (&__pyx_v_kfilter->k_endog), (&__pyx_v_alpha), __pyx_v_kfilter->_tmp1, (&__pyx_v_kfilter->k_states), __pyx_v_kfilter->_tmp3, (&__pyx_v_kfilter->k_endog), (&__pyx_v_beta), __pyx_v_kfilter->_tmp0, (&__pyx_v_kfilter->k_states));

    /* "statsmodels\tsa\statespace\_statespace.pyx":629
 *         # $P_{t|t} = - 1.0 * \\# P_t + 1.0 * P_t$
 *         # $(m \times m) = (m \times m) (m \times m) + (m \times m)$
 *         sgemm("N", "N", &kfilter.k_states, &kfilter.k_states, &kfilter.k_states,             # <<<<<<<<<<<<<<
 *               &gamma, kfilter._tmp0, &kfilter.k_states,
 *                       kfilter._input_state_cov, &kfilter.k_states,
 */
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  /* "statsmodels\tsa\statespace\_statespace.pyx":634
 *               &alpha, kfilter._filtered_state_cov, &kfilter.k_states)
 * 
 *     return 0             # <<<<<<<<<<<<<<
 * 
 * cdef int sprediction_conventional(sKalmanFilter kfilter):
 */
  __pyx_r = 0;
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  /* "statsmodels\tsa\statespace\_statespace.pyx":593
 *     return 0
 * 
 * cdef int supdating_conventional(sKalmanFilter kfilter):             # <<<<<<<<<<<<<<
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/* "statsmodels\tsa\statespace\_statespace.pyx":636
 *     return 0
 * 
 * cdef int sprediction_conventional(sKalmanFilter kfilter):             # <<<<<<<<<<<<<<
 * 
 *     # Constants
 */

static int __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_sprediction_conventional(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_kfilter) {
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 *         np.float32_t beta = 0.0
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 *         np.float32_t beta = 0.0
 *         np.float32_t gamma = -1.0
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  /* "statsmodels\tsa\statespace\_statespace.pyx":642
 *         int inc = 1
 *         np.float32_t alpha = 1.0
 *         np.float32_t beta = 0.0             # <<<<<<<<<<<<<<
 *         np.float32_t gamma = -1.0
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 */
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  /* "statsmodels\tsa\statespace\_statespace.pyx":643
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 *         np.float32_t beta = 0.0
 *         np.float32_t gamma = -1.0             # <<<<<<<<<<<<<<
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  /* "statsmodels\tsa\statespace\_statespace.pyx":647
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 *     # $a_{t+1} = T_t a_{t|t} + c_t$
 *     scopy(&kfilter.k_states, kfilter._state_intercept, &inc, kfilter._predicted_state, &inc)             # <<<<<<<<<<<<<<
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 */
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  /* "statsmodels\tsa\statespace\_statespace.pyx":648
 *     # $a_{t+1} = T_t a_{t|t} + c_t$
 *     scopy(&kfilter.k_states, kfilter._state_intercept, &inc, kfilter._predicted_state, &inc)
 *     sgemv("N", &kfilter.k_states, &kfilter.k_states,             # <<<<<<<<<<<<<<
 *           &alpha, kfilter._transition, &kfilter.k_states,
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 */
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  /* "statsmodels\tsa\statespace\_statespace.pyx":658
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 *     # converged == True
 *     if not kfilter.converged:             # <<<<<<<<<<<<<<
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 */
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 *     return 0             # <<<<<<<<<<<<<<
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 * 
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 * 
 * cdef int sprediction_conventional(sKalmanFilter kfilter):             # <<<<<<<<<<<<<<
 * 
 *     # Constants
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/* "statsmodels\tsa\statespace\_statespace.pyx":679
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 * 
 * cdef np.float32_t sloglikelihood_conventional(sKalmanFilter kfilter, np.float32_t determinant):             # <<<<<<<<<<<<<<
 *     # Constants
 *     cdef:
 */

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 *         # Continue taking the inverse
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 *         # Copy initialization arrays to input arrays if we're starting the
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 * 
 *     cdef void initialize_function_pointers(self) except *:             # <<<<<<<<<<<<<<
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 * 
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/* "statsmodels\tsa\statespace\_statespace.pyx":1566
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 * 
 *     cdef void _select_missing_entire_obs(self):             # <<<<<<<<<<<<<<
 *         cdef:
 *             int i, j
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static void __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter__select_missing_entire_obs(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self) {
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 *         for i in range(self.model.k_states):
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 *         self._design = &self.selected_design[0]             # <<<<<<<<<<<<<<
 * 
 *         # Change the forecasting step to set the forecast at the intercept
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 *         # $d_t$, so that the forecast error is $v_t = y_t - d_t$.
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 *         # Change the updating step to just copy $a_{t|t} = a_t$ and
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 * 
 *         # Change the inversion step to inverse to nans.
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 *         # Change the loglikelihood calculation to give zero.
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 * 
 *     cdef void _select_missing_entire_obs(self):             # <<<<<<<<<<<<<<
 *         cdef:
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/* "statsmodels\tsa\statespace\_statespace.pyx":1602
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 *         cdef:
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static void __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter__select_missing_partial_obs(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self) {
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 *             int obs_cov_t = 0
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 *             int design_t = 0
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 *         # Mark as not converged so that it does not inappropriately
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 *         # copy over steady state matrices
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 * 
 *         # Set dimensions
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 *         # Set dimensions
 *         self.k_endog = self.model.k_endog - self.model.nmissing[self.t]
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 * 
 *         if self.model.design.shape[2] > 1: design_t = self.t             # <<<<<<<<<<<<<<
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 *         k = 0             # <<<<<<<<<<<<<<
 *         for i in range(self.model.k_endog):
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 * 
 *         k = 0
 *         for i in range(self.model.k_endog):             # <<<<<<<<<<<<<<
 *             if not self.model.missing[i, self.t]:
 * 
 */
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    /* "statsmodels\tsa\statespace\_statespace.pyx":1622
 *         k = 0
 *         for i in range(self.model.k_endog):
 *             if not self.model.missing[i, self.t]:             # <<<<<<<<<<<<<<
 * 
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 *             if not self.model.missing[i, self.t]:
 * 
 *                 self.selected_obs[k] = self.model.obs[i, self.t]             # <<<<<<<<<<<<<<
 * 
 *                 # i is rows
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 *                 scopy(&self.model.k_states,
 *                       &self.model.design[i, 0, design_t], &self.model.k_endog,             # <<<<<<<<<<<<<<
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 * 
 */
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      __pyx_t_11 = 0;
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 *                 scopy(&self.model.k_states,
 *                       &self.model.design[i, 0, design_t], &self.model.k_endog,
 *                       &self.selected_design[k], &self.k_endog)             # <<<<<<<<<<<<<<
 * 
 *                 # i, k is columns
 */
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      /* "statsmodels\tsa\statespace\_statespace.pyx":1628
 *                 # i is rows
 *                 # k is rows
 *                 scopy(&self.model.k_states,             # <<<<<<<<<<<<<<
 *                       &self.model.design[i, 0, design_t], &self.model.k_endog,
 *                       &self.selected_design[k], &self.k_endog)
 */
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 *                 # i, k is columns
 *                 # j, l is rows
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 *                 for j in range(self.model.k_endog):
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 *                 # j, l is rows
 *                 l = 0
 *                 for j in range(self.model.k_endog):             # <<<<<<<<<<<<<<
 *                     if not self.model.missing[j, self.t]:
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 *                 for j in range(self.model.k_endog):
 *                     if not self.model.missing[j, self.t]:             # <<<<<<<<<<<<<<
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 *             int inc = 1
 *             np.float32_t alpha = 1.0
 *             np.float32_t beta = 0.0             # <<<<<<<<<<<<<<
 *             np.float32_t gamma = -1.0
 *         # Indices for arrays that may or may not be stored completely
 */
  __pyx_v_beta = 0.0;

  /* "statsmodels\tsa\statespace\_statespace.pyx":1688
 *             np.float32_t alpha = 1.0
 *             np.float32_t beta = 0.0
 *             np.float32_t gamma = -1.0             # <<<<<<<<<<<<<<
 *         # Indices for arrays that may or may not be stored completely
 *         cdef:
 */
  __pyx_v_gamma = -1.0;

  /* "statsmodels\tsa\statespace\_statespace.pyx":1691
 *         # Indices for arrays that may or may not be stored completely
 *         cdef:
 *             int forecast_t = self.t             # <<<<<<<<<<<<<<
 *             int filtered_t = self.t
 *             int predicted_t = self.t
 */
  __pyx_t_1 = __pyx_v_self->t;
  __pyx_v_forecast_t = __pyx_t_1;

  /* "statsmodels\tsa\statespace\_statespace.pyx":1692
 *         cdef:
 *             int forecast_t = self.t
 *             int filtered_t = self.t             # <<<<<<<<<<<<<<
 *             int predicted_t = self.t
 *         if self.conserve_memory & MEMORY_NO_FORECAST > 0:
 */
  __pyx_t_1 = __pyx_v_self->t;
  __pyx_v_filtered_t = __pyx_t_1;

  /* "statsmodels\tsa\statespace\_statespace.pyx":1693
 *             int forecast_t = self.t
 *             int filtered_t = self.t
 *             int predicted_t = self.t             # <<<<<<<<<<<<<<
 *         if self.conserve_memory & MEMORY_NO_FORECAST > 0:
 *             forecast_t = 1
 */
  __pyx_t_1 = __pyx_v_self->t;
  __pyx_v_predicted_t = __pyx_t_1;

  /* "statsmodels\tsa\statespace\_statespace.pyx":1694
 *             int filtered_t = self.t
 *             int predicted_t = self.t
 *         if self.conserve_memory & MEMORY_NO_FORECAST > 0:             # <<<<<<<<<<<<<<
 *             forecast_t = 1
 *         if self.conserve_memory & MEMORY_NO_FILTERED > 0:
 */
  __pyx_t_2 = (((__pyx_v_self->conserve_memory & __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_MEMORY_NO_FORECAST) > 0) != 0);
  if (__pyx_t_2) {

    /* "statsmodels\tsa\statespace\_statespace.pyx":1695
 *             int predicted_t = self.t
 *         if self.conserve_memory & MEMORY_NO_FORECAST > 0:
 *             forecast_t = 1             # <<<<<<<<<<<<<<
 *         if self.conserve_memory & MEMORY_NO_FILTERED > 0:
 *             filtered_t = 1
 */
    __pyx_v_forecast_t = 1;
    goto __pyx_L3;
  }
  __pyx_L3:;

  /* "statsmodels\tsa\statespace\_statespace.pyx":1696
 *         if self.conserve_memory & MEMORY_NO_FORECAST > 0:
 *             forecast_t = 1
 *         if self.conserve_memory & MEMORY_NO_FILTERED > 0:             # <<<<<<<<<<<<<<
 *             filtered_t = 1
 *         if self.conserve_memory & MEMORY_NO_PREDICTED > 0:
 */
  __pyx_t_2 = (((__pyx_v_self->conserve_memory & __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_MEMORY_NO_FILTERED) > 0) != 0);
  if (__pyx_t_2) {

    /* "statsmodels\tsa\statespace\_statespace.pyx":1697
 *             forecast_t = 1
 *         if self.conserve_memory & MEMORY_NO_FILTERED > 0:
 *             filtered_t = 1             # <<<<<<<<<<<<<<
 *         if self.conserve_memory & MEMORY_NO_PREDICTED > 0:
 *             predicted_t = 1
 */
    __pyx_v_filtered_t = 1;
    goto __pyx_L4;
  }
  __pyx_L4:;

  /* "statsmodels\tsa\statespace\_statespace.pyx":1698
 *         if self.conserve_memory & MEMORY_NO_FILTERED > 0:
 *             filtered_t = 1
 *         if self.conserve_memory & MEMORY_NO_PREDICTED > 0:             # <<<<<<<<<<<<<<
 *             predicted_t = 1
 * 
 */
  __pyx_t_2 = (((__pyx_v_self->conserve_memory & __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_MEMORY_NO_PREDICTED) > 0) != 0);
  if (__pyx_t_2) {

    /* "statsmodels\tsa\statespace\_statespace.pyx":1699
 *             filtered_t = 1
 *         if self.conserve_memory & MEMORY_NO_PREDICTED > 0:
 *             predicted_t = 1             # <<<<<<<<<<<<<<
 * 
 *         if self.time_invariant and not self.converged and self.model.nmissing[self.t] == 0:
 */
    __pyx_v_predicted_t = 1;
    goto __pyx_L5;
  }
  __pyx_L5:;

  /* "statsmodels\tsa\statespace\_statespace.pyx":1701
 *             predicted_t = 1
 * 
 *         if self.time_invariant and not self.converged and self.model.nmissing[self.t] == 0:             # <<<<<<<<<<<<<<
 *             # #### Check for steady-state convergence
 *             #
 */
  __pyx_t_3 = (__pyx_v_self->time_invariant != 0);
  if (__pyx_t_3) {
  } else {
    __pyx_t_2 = __pyx_t_3;
    goto __pyx_L7_bool_binop_done;
  }
  __pyx_t_3 = ((!(__pyx_v_self->converged != 0)) != 0);
  if (__pyx_t_3) {
  } else {
    __pyx_t_2 = __pyx_t_3;
    goto __pyx_L7_bool_binop_done;
  }
  if (unlikely(!__pyx_v_self->model->nmissing.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 1701; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
  __pyx_t_1 = __pyx_v_self->t;
  __pyx_t_3 = (((*((int *) ( /* dim=0 */ (__pyx_v_self->model->nmissing.data + __pyx_t_1 * __pyx_v_self->model->nmissing.strides[0]) ))) == 0) != 0);
  __pyx_t_2 = __pyx_t_3;
  __pyx_L7_bool_binop_done:;
  if (__pyx_t_2) {

    /* "statsmodels\tsa\statespace\_statespace.pyx":1706
 *             # `tmp0` array used here, dimension $(m \times m)$
 *             # `tmp1` array used here, dimension $(1 \times 1)$
 *             scopy(&self.k_states2, self._input_state_cov, &inc, self._tmp0, &inc)             # <<<<<<<<<<<<<<
 *             saxpy(&self.k_states2, &gamma, self._predicted_state_cov, &inc, self._tmp0, &inc)
 * 
 */
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_scopy((&__pyx_v_self->k_states2), __pyx_v_self->_input_state_cov, (&__pyx_v_inc), __pyx_v_self->_tmp0, (&__pyx_v_inc));

    /* "statsmodels\tsa\statespace\_statespace.pyx":1707
 *             # `tmp1` array used here, dimension $(1 \times 1)$
 *             scopy(&self.k_states2, self._input_state_cov, &inc, self._tmp0, &inc)
 *             saxpy(&self.k_states2, &gamma, self._predicted_state_cov, &inc, self._tmp0, &inc)             # <<<<<<<<<<<<<<
 * 
 *             if sdot(&self.k_states2, self._tmp0, &inc, self._tmp0, &inc) < self.tolerance:
 */
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_saxpy((&__pyx_v_self->k_states2), (&__pyx_v_gamma), __pyx_v_self->_predicted_state_cov, (&__pyx_v_inc), __pyx_v_self->_tmp0, (&__pyx_v_inc));

    /* "statsmodels\tsa\statespace\_statespace.pyx":1709
 *             saxpy(&self.k_states2, &gamma, self._predicted_state_cov, &inc, self._tmp0, &inc)
 * 
 *             if sdot(&self.k_states2, self._tmp0, &inc, self._tmp0, &inc) < self.tolerance:             # <<<<<<<<<<<<<<
 *                 self.converged = 1
 *                 self.period_converged = self.t
 */
    __pyx_t_2 = ((__pyx_v_11statsmodels_3tsa_10statespace_11_statespace_sdot((&__pyx_v_self->k_states2), __pyx_v_self->_tmp0, (&__pyx_v_inc), __pyx_v_self->_tmp0, (&__pyx_v_inc)) < __pyx_v_self->tolerance) != 0);
    if (__pyx_t_2) {

      /* "statsmodels\tsa\statespace\_statespace.pyx":1710
 * 
 *             if sdot(&self.k_states2, self._tmp0, &inc, self._tmp0, &inc) < self.tolerance:
 *                 self.converged = 1             # <<<<<<<<<<<<<<
 *                 self.period_converged = self.t
 * 
 */
      __pyx_v_self->converged = 1;

      /* "statsmodels\tsa\statespace\_statespace.pyx":1711
 *             if sdot(&self.k_states2, self._tmp0, &inc, self._tmp0, &inc) < self.tolerance:
 *                 self.converged = 1
 *                 self.period_converged = self.t             # <<<<<<<<<<<<<<
 * 
 * 
 */
      __pyx_t_4 = __pyx_v_self->t;
      __pyx_v_self->period_converged = __pyx_t_4;
      goto __pyx_L10;
    }
    __pyx_L10:;

    /* "statsmodels\tsa\statespace\_statespace.pyx":1716
 *             # If we just converged, copy the current iteration matrices to the
 *             # converged storage
 *             if self.converged == 1:             # <<<<<<<<<<<<<<
 *                 # $F_t$
 *                 scopy(&self.k_endog2, &self.forecast_error_cov[0, 0, forecast_t], &inc, self._converged_forecast_error_cov, &inc)
 */
    __pyx_t_2 = ((__pyx_v_self->converged == 1) != 0);
    if (__pyx_t_2) {

      /* "statsmodels\tsa\statespace\_statespace.pyx":1718
 *             if self.converged == 1:
 *                 # $F_t$
 *                 scopy(&self.k_endog2, &self.forecast_error_cov[0, 0, forecast_t], &inc, self._converged_forecast_error_cov, &inc)             # <<<<<<<<<<<<<<
 *                 # $P_{t|t}$
 *                 scopy(&self.k_states2, &self.filtered_state_cov[0, 0, filtered_t], &inc, self._converged_filtered_state_cov, &inc)
 */
      if (unlikely(!__pyx_v_self->forecast_error_cov.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 1718; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
      __pyx_t_5 = 0;
      __pyx_t_6 = 0;
      __pyx_t_4 = __pyx_v_forecast_t;
      __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_scopy((&__pyx_v_self->k_endog2), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=2 */ (( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_self->forecast_error_cov.data) + __pyx_t_5)) ) + __pyx_t_6 * __pyx_v_self->forecast_error_cov.strides[1]) ) + __pyx_t_4 * __pyx_v_self->forecast_error_cov.strides[2]) )))), (&__pyx_v_inc), __pyx_v_self->_converged_forecast_error_cov, (&__pyx_v_inc));

      /* "statsmodels\tsa\statespace\_statespace.pyx":1720
 *                 scopy(&self.k_endog2, &self.forecast_error_cov[0, 0, forecast_t], &inc, self._converged_forecast_error_cov, &inc)
 *                 # $P_{t|t}$
 *                 scopy(&self.k_states2, &self.filtered_state_cov[0, 0, filtered_t], &inc, self._converged_filtered_state_cov, &inc)             # <<<<<<<<<<<<<<
 *                 # $P_t$
 *                 scopy(&self.k_states2, &self.predicted_state_cov[0, 0, predicted_t], &inc, self._converged_predicted_state_cov, &inc)
 */
      if (unlikely(!__pyx_v_self->filtered_state_cov.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 1720; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
      __pyx_t_7 = 0;
      __pyx_t_8 = 0;
      __pyx_t_9 = __pyx_v_filtered_t;
      __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_scopy((&__pyx_v_self->k_states2), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=2 */ (( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_self->filtered_state_cov.data) + __pyx_t_7)) ) + __pyx_t_8 * __pyx_v_self->filtered_state_cov.strides[1]) ) + __pyx_t_9 * __pyx_v_self->filtered_state_cov.strides[2]) )))), (&__pyx_v_inc), __pyx_v_self->_converged_filtered_state_cov, (&__pyx_v_inc));

      /* "statsmodels\tsa\statespace\_statespace.pyx":1722
 *                 scopy(&self.k_states2, &self.filtered_state_cov[0, 0, filtered_t], &inc, self._converged_filtered_state_cov, &inc)
 *                 # $P_t$
 *                 scopy(&self.k_states2, &self.predicted_state_cov[0, 0, predicted_t], &inc, self._converged_predicted_state_cov, &inc)             # <<<<<<<<<<<<<<
 *                 # $|F_t|$
 *                 self.converged_determinant = self.determinant
 */
      if (unlikely(!__pyx_v_self->predicted_state_cov.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 1722; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
      __pyx_t_10 = 0;
      __pyx_t_11 = 0;
      __pyx_t_12 = __pyx_v_predicted_t;
      __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_scopy((&__pyx_v_self->k_states2), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=2 */ (( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_self->predicted_state_cov.data) + __pyx_t_10)) ) + __pyx_t_11 * __pyx_v_self->predicted_state_cov.strides[1]) ) + __pyx_t_12 * __pyx_v_self->predicted_state_cov.strides[2]) )))), (&__pyx_v_inc), __pyx_v_self->_converged_predicted_state_cov, (&__pyx_v_inc));

      /* "statsmodels\tsa\statespace\_statespace.pyx":1724
 *                 scopy(&self.k_states2, &self.predicted_state_cov[0, 0, predicted_t], &inc, self._converged_predicted_state_cov, &inc)
 *                 # $|F_t|$
 *                 self.converged_determinant = self.determinant             # <<<<<<<<<<<<<<
 * 
 *     cdef void migrate_storage(self):
 */
      __pyx_t_13 = __pyx_v_self->determinant;
      __pyx_v_self->converged_determinant = __pyx_t_13;
      goto __pyx_L11;
    }
    __pyx_L11:;
    goto __pyx_L6;
  }
  __pyx_L6:;

  /* "statsmodels\tsa\statespace\_statespace.pyx":1682
 *                     self.predicted_state_cov[j,i,predicted_t+1] = value
 * 
 *     cdef void check_convergence(self):             # <<<<<<<<<<<<<<
 *         # Constants
 *         cdef:
 */

  /* function exit code */
  goto __pyx_L0;
  __pyx_L1_error:;
  __Pyx_WriteUnraisable("statsmodels.tsa.statespace._statespace.sKalmanFilter.check_convergence", __pyx_clineno, __pyx_lineno, __pyx_filename, 0);
  __pyx_L0:;
  __Pyx_RefNannyFinishContext();
}

/* "statsmodels\tsa\statespace\_statespace.pyx":1726
 *                 self.converged_determinant = self.determinant
 * 
 *     cdef void migrate_storage(self):             # <<<<<<<<<<<<<<
 *         cdef int inc = 1
 * 
 */

static void __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_migrate_storage(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *__pyx_v_self) {
  int __pyx_v_inc;
  __Pyx_RefNannyDeclarations
  int __pyx_t_1;
  Py_ssize_t __pyx_t_2;
  Py_ssize_t __pyx_t_3;
  Py_ssize_t __pyx_t_4;
  Py_ssize_t __pyx_t_5;
  Py_ssize_t __pyx_t_6;
  Py_ssize_t __pyx_t_7;
  Py_ssize_t __pyx_t_8;
  Py_ssize_t __pyx_t_9;
  Py_ssize_t __pyx_t_10;
  Py_ssize_t __pyx_t_11;
  Py_ssize_t __pyx_t_12;
  Py_ssize_t __pyx_t_13;
  Py_ssize_t __pyx_t_14;
  Py_ssize_t __pyx_t_15;
  Py_ssize_t __pyx_t_16;
  Py_ssize_t __pyx_t_17;
  Py_ssize_t __pyx_t_18;
  Py_ssize_t __pyx_t_19;
  Py_ssize_t __pyx_t_20;
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  Py_ssize_t __pyx_t_25;
  Py_ssize_t __pyx_t_26;
  Py_ssize_t __pyx_t_27;
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  Py_ssize_t __pyx_t_29;
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  Py_ssize_t __pyx_t_31;
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  Py_ssize_t __pyx_t_33;
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  Py_ssize_t __pyx_t_35;
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  Py_ssize_t __pyx_t_39;
  Py_ssize_t __pyx_t_40;
  Py_ssize_t __pyx_t_41;
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  Py_ssize_t __pyx_t_43;
  Py_ssize_t __pyx_t_44;
  Py_ssize_t __pyx_t_45;
  int __pyx_lineno = 0;
  const char *__pyx_filename = NULL;
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  /* "statsmodels\tsa\statespace\_statespace.pyx":1727
 * 
 *     cdef void migrate_storage(self):
 *         cdef int inc = 1             # <<<<<<<<<<<<<<
 * 
 *         # Forecast: 1 -> 0
 */
  __pyx_v_inc = 1;

  /* "statsmodels\tsa\statespace\_statespace.pyx":1730
 * 
 *         # Forecast: 1 -> 0
 *         if self.conserve_memory & MEMORY_NO_FORECAST > 0:             # <<<<<<<<<<<<<<
 *             scopy(&self.k_endog, &self.forecast[0, 1], &inc, &self.forecast[0, 0], &inc)
 *             scopy(&self.k_endog, &self.forecast_error[0, 1], &inc, &self.forecast_error[0, 0], &inc)
 */
  __pyx_t_1 = (((__pyx_v_self->conserve_memory & __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_MEMORY_NO_FORECAST) > 0) != 0);
  if (__pyx_t_1) {

    /* "statsmodels\tsa\statespace\_statespace.pyx":1731
 *         # Forecast: 1 -> 0
 *         if self.conserve_memory & MEMORY_NO_FORECAST > 0:
 *             scopy(&self.k_endog, &self.forecast[0, 1], &inc, &self.forecast[0, 0], &inc)             # <<<<<<<<<<<<<<
 *             scopy(&self.k_endog, &self.forecast_error[0, 1], &inc, &self.forecast_error[0, 0], &inc)
 *             scopy(&self.k_endog2, &self.forecast_error_cov[0, 0, 1], &inc, &self.forecast_error_cov[0, 0, 0], &inc)
 */
    if (unlikely(!__pyx_v_self->forecast.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 1731; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
    __pyx_t_2 = 0;
    __pyx_t_3 = 1;
    if (unlikely(!__pyx_v_self->forecast.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 1731; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
    __pyx_t_4 = 0;
    __pyx_t_5 = 0;
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_scopy((&__pyx_v_self->k_endog), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_self->forecast.data) + __pyx_t_2)) ) + __pyx_t_3 * __pyx_v_self->forecast.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_self->forecast.data) + __pyx_t_4)) ) + __pyx_t_5 * __pyx_v_self->forecast.strides[1]) )))), (&__pyx_v_inc));

    /* "statsmodels\tsa\statespace\_statespace.pyx":1732
 *         if self.conserve_memory & MEMORY_NO_FORECAST > 0:
 *             scopy(&self.k_endog, &self.forecast[0, 1], &inc, &self.forecast[0, 0], &inc)
 *             scopy(&self.k_endog, &self.forecast_error[0, 1], &inc, &self.forecast_error[0, 0], &inc)             # <<<<<<<<<<<<<<
 *             scopy(&self.k_endog2, &self.forecast_error_cov[0, 0, 1], &inc, &self.forecast_error_cov[0, 0, 0], &inc)
 * 
 */
    if (unlikely(!__pyx_v_self->forecast_error.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 1732; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
    __pyx_t_6 = 0;
    __pyx_t_7 = 1;
    if (unlikely(!__pyx_v_self->forecast_error.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 1732; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
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  __pyx_t_11 = 0;
  __pyx_t_12 = 0;
  __pyx_t_13 = 0;
  __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_scopy((&__pyx_v_k_endog2), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_error_variance.data) + __pyx_t_10)) ) + __pyx_t_11 * __pyx_v_error_variance.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_forward_variance.data) + __pyx_t_12)) ) + __pyx_t_13 * __pyx_v_forward_variance.strides[1]) )))), (&__pyx_v_inc));

  /* "statsmodels\tsa\statespace\_statespace.pyx":1831
 * 
 *     scopy(&k_endog2, &error_variance[0,0], &inc, &forward_variance[0,0], &inc)   # \Sigma_s
 *     scopy(&k_endog2, &error_variance[0,0], &inc, &backward_variance[0,0], &inc)  # \Sigma_s^*,  s = 0, ..., p             # <<<<<<<<<<<<<<
 *     scopy(&k_endog2, &error_variance[0,0], &inc, &autocovariances[0,0], &inc)  # \Gamma_s
 * 
 */
  __pyx_t_14 = 0;
  __pyx_t_15 = 0;
  __pyx_t_16 = 0;
  __pyx_t_17 = 0;
  __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_scopy((&__pyx_v_k_endog2), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_error_variance.data) + __pyx_t_14)) ) + __pyx_t_15 * __pyx_v_error_variance.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_backward_variance.data) + __pyx_t_16)) ) + __pyx_t_17 * __pyx_v_backward_variance.strides[1]) )))), (&__pyx_v_inc));

  /* "statsmodels\tsa\statespace\_statespace.pyx":1832
 *     scopy(&k_endog2, &error_variance[0,0], &inc, &forward_variance[0,0], &inc)   # \Sigma_s
 *     scopy(&k_endog2, &error_variance[0,0], &inc, &backward_variance[0,0], &inc)  # \Sigma_s^*,  s = 0, ..., p
 *     scopy(&k_endog2, &error_variance[0,0], &inc, &autocovariances[0,0], &inc)  # \Gamma_s             # <<<<<<<<<<<<<<
 * 
 *     # error_variance_factor = linalg.cholesky(error_variance, lower=True)
 */
  __pyx_t_18 = 0;
  __pyx_t_19 = 0;
  __pyx_t_20 = 0;
  __pyx_t_21 = 0;
  __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_scopy((&__pyx_v_k_endog2), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_error_variance.data) + __pyx_t_18)) ) + __pyx_t_19 * __pyx_v_error_variance.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_autocovariances.data) + __pyx_t_20)) ) + __pyx_t_21 * __pyx_v_autocovariances.strides[1]) )))), (&__pyx_v_inc));

  /* "statsmodels\tsa\statespace\_statespace.pyx":1835
 * 
 *     # error_variance_factor = linalg.cholesky(error_variance, lower=True)
 *     scopy(&k_endog2, &error_variance[0,0], &inc, &forward_factors[0,0], &inc)             # <<<<<<<<<<<<<<
 *     spotrf("L", &k_endog, &forward_factors[0,0], &k_endog, &info)
 *     scopy(&k_endog2, &forward_factors[0,0], &inc, &backward_factors[0,0], &inc)
 */
  __pyx_t_22 = 0;
  __pyx_t_23 = 0;
  __pyx_t_24 = 0;
  __pyx_t_25 = 0;
  __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_scopy((&__pyx_v_k_endog2), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_error_variance.data) + __pyx_t_22)) ) + __pyx_t_23 * __pyx_v_error_variance.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_forward_factors.data) + __pyx_t_24)) ) + __pyx_t_25 * __pyx_v_forward_factors.strides[1]) )))), (&__pyx_v_inc));

  /* "statsmodels\tsa\statespace\_statespace.pyx":1836
 *     # error_variance_factor = linalg.cholesky(error_variance, lower=True)
 *     scopy(&k_endog2, &error_variance[0,0], &inc, &forward_factors[0,0], &inc)
 *     spotrf("L", &k_endog, &forward_factors[0,0], &k_endog, &info)             # <<<<<<<<<<<<<<
 *     scopy(&k_endog2, &forward_factors[0,0], &inc, &backward_factors[0,0], &inc)
 * 
 */
  __pyx_t_26 = 0;
  __pyx_t_27 = 0;
  __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_spotrf(__pyx_k_L, (&__pyx_v_k_endog), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_forward_factors.data) + __pyx_t_26)) ) + __pyx_t_27 * __pyx_v_forward_factors.strides[1]) )))), (&__pyx_v_k_endog), (&__pyx_v_info));

  /* "statsmodels\tsa\statespace\_statespace.pyx":1837
 *     scopy(&k_endog2, &error_variance[0,0], &inc, &forward_factors[0,0], &inc)
 *     spotrf("L", &k_endog, &forward_factors[0,0], &k_endog, &info)
 *     scopy(&k_endog2, &forward_factors[0,0], &inc, &backward_factors[0,0], &inc)             # <<<<<<<<<<<<<<
 * 
 *     # We fill in the entries as follows:
 */
  __pyx_t_28 = 0;
  __pyx_t_29 = 0;
  __pyx_t_30 = 0;
  __pyx_t_31 = 0;
  __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_scopy((&__pyx_v_k_endog2), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_forward_factors.data) + __pyx_t_28)) ) + __pyx_t_29 * __pyx_v_forward_factors.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_backward_factors.data) + __pyx_t_30)) ) + __pyx_t_31 * __pyx_v_backward_factors.strides[1]) )))), (&__pyx_v_inc));

  /* "statsmodels\tsa\statespace\_statespace.pyx":1846
 *     # [p,p], [p,1], ..., [p,p-1]
 *     # the last row, correctly ordered, is then used as the coefficients
 *     for s in range(order):  # s = 0, ..., p-1             # <<<<<<<<<<<<<<
 *         if s % 2 == 0:
 *             forwards = &forwards1[0, 0]
 */
  __pyx_t_32 = __pyx_v_order;
  for (__pyx_t_33 = 0; __pyx_t_33 < __pyx_t_32; __pyx_t_33+=1) {
    __pyx_v_s = __pyx_t_33;

    /* "statsmodels\tsa\statespace\_statespace.pyx":1847
 *     # the last row, correctly ordered, is then used as the coefficients
 *     for s in range(order):  # s = 0, ..., p-1
 *         if s % 2 == 0:             # <<<<<<<<<<<<<<
 *             forwards = &forwards1[0, 0]
 *             prev_forwards = &forwards2[0, 0]
 */
    __pyx_t_3 = ((__Pyx_mod_long(__pyx_v_s, 2) == 0) != 0);
    if (__pyx_t_3) {

      /* "statsmodels\tsa\statespace\_statespace.pyx":1848
 *     for s in range(order):  # s = 0, ..., p-1
 *         if s % 2 == 0:
 *             forwards = &forwards1[0, 0]             # <<<<<<<<<<<<<<
 *             prev_forwards = &forwards2[0, 0]
 *             backwards = &backwards1[0, 0]
 */
      __pyx_t_34 = 0;
      __pyx_t_35 = 0;
      __pyx_v_forwards = (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_forwards1.data) + __pyx_t_34)) ) + __pyx_t_35 * __pyx_v_forwards1.strides[1]) ))));

      /* "statsmodels\tsa\statespace\_statespace.pyx":1849
 *         if s % 2 == 0:
 *             forwards = &forwards1[0, 0]
 *             prev_forwards = &forwards2[0, 0]             # <<<<<<<<<<<<<<
 *             backwards = &backwards1[0, 0]
 *             prev_backwards = &backwards2[0, 0]
 */
      __pyx_t_36 = 0;
      __pyx_t_37 = 0;
      __pyx_v_prev_forwards = (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_forwards2.data) + __pyx_t_36)) ) + __pyx_t_37 * __pyx_v_forwards2.strides[1]) ))));

      /* "statsmodels\tsa\statespace\_statespace.pyx":1850
 *             forwards = &forwards1[0, 0]
 *             prev_forwards = &forwards2[0, 0]
 *             backwards = &backwards1[0, 0]             # <<<<<<<<<<<<<<
 *             prev_backwards = &backwards2[0, 0]
 *         else:
 */
      __pyx_t_38 = 0;
      __pyx_t_39 = 0;
      __pyx_v_backwards = (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_backwards1.data) + __pyx_t_38)) ) + __pyx_t_39 * __pyx_v_backwards1.strides[1]) ))));

      /* "statsmodels\tsa\statespace\_statespace.pyx":1851
 *             prev_forwards = &forwards2[0, 0]
 *             backwards = &backwards1[0, 0]
 *             prev_backwards = &backwards2[0, 0]             # <<<<<<<<<<<<<<
 *         else:
 *             forwards = &forwards2[0, 0]
 */
      __pyx_t_40 = 0;
      __pyx_t_41 = 0;
      __pyx_v_prev_backwards = (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_backwards2.data) + __pyx_t_40)) ) + __pyx_t_41 * __pyx_v_backwards2.strides[1]) ))));
      goto __pyx_L6;
    }
    /*else*/ {

      /* "statsmodels\tsa\statespace\_statespace.pyx":1853
 *             prev_backwards = &backwards2[0, 0]
 *         else:
 *             forwards = &forwards2[0, 0]             # <<<<<<<<<<<<<<
 *             prev_forwards = &forwards1[0, 0]
 *             backwards = &backwards2[0, 0]
 */
      __pyx_t_42 = 0;
      __pyx_t_43 = 0;
      __pyx_v_forwards = (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_forwards2.data) + __pyx_t_42)) ) + __pyx_t_43 * __pyx_v_forwards2.strides[1]) ))));

      /* "statsmodels\tsa\statespace\_statespace.pyx":1854
 *         else:
 *             forwards = &forwards2[0, 0]
 *             prev_forwards = &forwards1[0, 0]             # <<<<<<<<<<<<<<
 *             backwards = &backwards2[0, 0]
 *             prev_backwards = &backwards1[0, 0]
 */
      __pyx_t_44 = 0;
      __pyx_t_45 = 0;
      __pyx_v_prev_forwards = (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_forwards1.data) + __pyx_t_44)) ) + __pyx_t_45 * __pyx_v_forwards1.strides[1]) ))));

      /* "statsmodels\tsa\statespace\_statespace.pyx":1855
 *             forwards = &forwards2[0, 0]
 *             prev_forwards = &forwards1[0, 0]
 *             backwards = &backwards2[0, 0]             # <<<<<<<<<<<<<<
 *             prev_backwards = &backwards1[0, 0]
 * 
 */
      __pyx_t_46 = 0;
      __pyx_t_47 = 0;
      __pyx_v_backwards = (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_backwards2.data) + __pyx_t_46)) ) + __pyx_t_47 * __pyx_v_backwards2.strides[1]) ))));

      /* "statsmodels\tsa\statespace\_statespace.pyx":1856
 *             prev_forwards = &forwards1[0, 0]
 *             backwards = &backwards2[0, 0]
 *             prev_backwards = &backwards1[0, 0]             # <<<<<<<<<<<<<<
 * 
 *         # Create the "last" (k = s+1) matrix
 */
      __pyx_t_48 = 0;
      __pyx_t_49 = 0;
      __pyx_v_prev_backwards = (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_backwards1.data) + __pyx_t_48)) ) + __pyx_t_49 * __pyx_v_backwards1.strides[1]) ))));
    }
    __pyx_L6:;

    /* "statsmodels\tsa\statespace\_statespace.pyx":1870
 *         #         lower=True, trans='T').T
 *         # )
 *         for k in range(k_endog):             # <<<<<<<<<<<<<<
 *             scopy(&k_endog, &partial_autocorrelations[k,s*k_endog], &k_endog, &tmp[0, k], &inc)
 *         strtrs("L", "T", "N", &k_endog, &k_endog, &backward_factors[0,0], &k_endog,
 */
    __pyx_t_50 = __pyx_v_k_endog;
    for (__pyx_t_51 = 0; __pyx_t_51 < __pyx_t_50; __pyx_t_51+=1) {
      __pyx_v_k = __pyx_t_51;

      /* "statsmodels\tsa\statespace\_statespace.pyx":1871
 *         # )
 *         for k in range(k_endog):
 *             scopy(&k_endog, &partial_autocorrelations[k,s*k_endog], &k_endog, &tmp[0, k], &inc)             # <<<<<<<<<<<<<<
 *         strtrs("L", "T", "N", &k_endog, &k_endog, &backward_factors[0,0], &k_endog,
 *                                                            &tmp[0, 0], &k_endog, &info)
 */
      __pyx_t_52 = __pyx_v_k;
      __pyx_t_53 = (__pyx_v_s * __pyx_v_k_endog);
      __pyx_t_54 = 0;
      __pyx_t_55 = __pyx_v_k;
      __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_scopy((&__pyx_v_k_endog), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_partial_autocorrelations.data) + __pyx_t_52)) ) + __pyx_t_53 * __pyx_v_partial_autocorrelations.strides[1]) )))), (&__pyx_v_k_endog), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_tmp.data) + __pyx_t_54)) ) + __pyx_t_55 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_inc));
    }

    /* "statsmodels\tsa\statespace\_statespace.pyx":1872
 *         for k in range(k_endog):
 *             scopy(&k_endog, &partial_autocorrelations[k,s*k_endog], &k_endog, &tmp[0, k], &inc)
 *         strtrs("L", "T", "N", &k_endog, &k_endog, &backward_factors[0,0], &k_endog,             # <<<<<<<<<<<<<<
 *                                                            &tmp[0, 0], &k_endog, &info)
 *         # sgemm("N", "T", &k_endog, &k_endog, &k_endog,
 */
    __pyx_t_56 = 0;
    __pyx_t_57 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":1873
 *             scopy(&k_endog, &partial_autocorrelations[k,s*k_endog], &k_endog, &tmp[0, k], &inc)
 *         strtrs("L", "T", "N", &k_endog, &k_endog, &backward_factors[0,0], &k_endog,
 *                                                            &tmp[0, 0], &k_endog, &info)             # <<<<<<<<<<<<<<
 *         # sgemm("N", "T", &k_endog, &k_endog, &k_endog,
 *         #   &alpha, &forward_factors[0,0], &k_endog,
 */
    __pyx_t_58 = 0;
    __pyx_t_59 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":1872
 *         for k in range(k_endog):
 *             scopy(&k_endog, &partial_autocorrelations[k,s*k_endog], &k_endog, &tmp[0, k], &inc)
 *         strtrs("L", "T", "N", &k_endog, &k_endog, &backward_factors[0,0], &k_endog,             # <<<<<<<<<<<<<<
 *                                                            &tmp[0, 0], &k_endog, &info)
 *         # sgemm("N", "T", &k_endog, &k_endog, &k_endog,
 */
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_strtrs(__pyx_k_L, __pyx_k_T, __pyx_k_N, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_backward_factors.data) + __pyx_t_56)) ) + __pyx_t_57 * __pyx_v_backward_factors.strides[1]) )))), (&__pyx_v_k_endog), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_tmp.data) + __pyx_t_58)) ) + __pyx_t_59 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_k_endog), (&__pyx_v_info));

    /* "statsmodels\tsa\statespace\_statespace.pyx":1879
 *         #   &beta, &forwards[s*k_endog2], &k_endog)
 *         strmm("R", "L", "T", "N", &k_endog, &k_endog,
 *           &alpha, &forward_factors[0,0], &k_endog,             # <<<<<<<<<<<<<<
 *                   &tmp[0, 0], &k_endog)
 *         for k in range(k_endog):
 */
    __pyx_t_60 = 0;
    __pyx_t_61 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":1880
 *         strmm("R", "L", "T", "N", &k_endog, &k_endog,
 *           &alpha, &forward_factors[0,0], &k_endog,
 *                   &tmp[0, 0], &k_endog)             # <<<<<<<<<<<<<<
 *         for k in range(k_endog):
 *             scopy(&k_endog, &tmp[k,0], &k_endog, &forwards[s*k_endog2 + k*k_endog], &inc)
 */
    __pyx_t_62 = 0;
    __pyx_t_63 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":1878
 *         #           &tmp[0, 0], &k_endog,
 *         #   &beta, &forwards[s*k_endog2], &k_endog)
 *         strmm("R", "L", "T", "N", &k_endog, &k_endog,             # <<<<<<<<<<<<<<
 *           &alpha, &forward_factors[0,0], &k_endog,
 *                   &tmp[0, 0], &k_endog)
 */
    __pyx_v_strmm(__pyx_k_R, __pyx_k_L, __pyx_k_T, __pyx_k_N, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_alpha), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_forward_factors.data) + __pyx_t_60)) ) + __pyx_t_61 * __pyx_v_forward_factors.strides[1]) )))), (&__pyx_v_k_endog), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_tmp.data) + __pyx_t_62)) ) + __pyx_t_63 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_k_endog));

    /* "statsmodels\tsa\statespace\_statespace.pyx":1881
 *           &alpha, &forward_factors[0,0], &k_endog,
 *                   &tmp[0, 0], &k_endog)
 *         for k in range(k_endog):             # <<<<<<<<<<<<<<
 *             scopy(&k_endog, &tmp[k,0], &k_endog, &forwards[s*k_endog2 + k*k_endog], &inc)
 * 
 */
    __pyx_t_50 = __pyx_v_k_endog;
    for (__pyx_t_51 = 0; __pyx_t_51 < __pyx_t_50; __pyx_t_51+=1) {
      __pyx_v_k = __pyx_t_51;

      /* "statsmodels\tsa\statespace\_statespace.pyx":1882
 *                   &tmp[0, 0], &k_endog)
 *         for k in range(k_endog):
 *             scopy(&k_endog, &tmp[k,0], &k_endog, &forwards[s*k_endog2 + k*k_endog], &inc)             # <<<<<<<<<<<<<<
 * 
 *         # P' L^{-1} = x
 */
      __pyx_t_64 = __pyx_v_k;
      __pyx_t_65 = 0;
      __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_scopy((&__pyx_v_k_endog), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_tmp.data) + __pyx_t_64)) ) + __pyx_t_65 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_k_endog), (&(__pyx_v_forwards[((__pyx_v_s * __pyx_v_k_endog2) + (__pyx_v_k * __pyx_v_k_endog))])), (&__pyx_v_inc));
    }

    /* "statsmodels\tsa\statespace\_statespace.pyx":1893
 *         #         lower=True, trans='T').T
 *         # )
 *         scopy(&k_endog2, &partial_autocorrelations[0, s*k_endog], &inc, &tmp[0, 0], &inc)             # <<<<<<<<<<<<<<
 *         strtrs("L", "T", "N", &k_endog, &k_endog, &forward_factors[0, 0], &k_endog,
 *                                                            &tmp[0, 0], &k_endog, &info)
 */
    __pyx_t_66 = 0;
    __pyx_t_50 = (__pyx_v_s * __pyx_v_k_endog);
    __pyx_t_67 = 0;
    __pyx_t_68 = 0;
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_scopy((&__pyx_v_k_endog2), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_partial_autocorrelations.data) + __pyx_t_66)) ) + __pyx_t_50 * __pyx_v_partial_autocorrelations.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_tmp.data) + __pyx_t_67)) ) + __pyx_t_68 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_inc));

    /* "statsmodels\tsa\statespace\_statespace.pyx":1894
 *         # )
 *         scopy(&k_endog2, &partial_autocorrelations[0, s*k_endog], &inc, &tmp[0, 0], &inc)
 *         strtrs("L", "T", "N", &k_endog, &k_endog, &forward_factors[0, 0], &k_endog,             # <<<<<<<<<<<<<<
 *                                                            &tmp[0, 0], &k_endog, &info)
 *         # sgemm("N", "T", &k_endog, &k_endog, &k_endog,
 */
    __pyx_t_69 = 0;
    __pyx_t_70 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":1895
 *         scopy(&k_endog2, &partial_autocorrelations[0, s*k_endog], &inc, &tmp[0, 0], &inc)
 *         strtrs("L", "T", "N", &k_endog, &k_endog, &forward_factors[0, 0], &k_endog,
 *                                                            &tmp[0, 0], &k_endog, &info)             # <<<<<<<<<<<<<<
 *         # sgemm("N", "T", &k_endog, &k_endog, &k_endog,
 *         #   &alpha, &backward_factors[0, 0], &k_endog,
 */
    __pyx_t_71 = 0;
    __pyx_t_72 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":1894
 *         # )
 *         scopy(&k_endog2, &partial_autocorrelations[0, s*k_endog], &inc, &tmp[0, 0], &inc)
 *         strtrs("L", "T", "N", &k_endog, &k_endog, &forward_factors[0, 0], &k_endog,             # <<<<<<<<<<<<<<
 *                                                            &tmp[0, 0], &k_endog, &info)
 *         # sgemm("N", "T", &k_endog, &k_endog, &k_endog,
 */
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_strtrs(__pyx_k_L, __pyx_k_T, __pyx_k_N, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_forward_factors.data) + __pyx_t_69)) ) + __pyx_t_70 * __pyx_v_forward_factors.strides[1]) )))), (&__pyx_v_k_endog), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_tmp.data) + __pyx_t_71)) ) + __pyx_t_72 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_k_endog), (&__pyx_v_info));

    /* "statsmodels\tsa\statespace\_statespace.pyx":1901
 *         #   &beta, &backwards[s * k_endog2], &k_endog)
 *         strmm("R", "L", "T", "N", &k_endog, &k_endog,
 *           &alpha, &backward_factors[0,0], &k_endog,             # <<<<<<<<<<<<<<
 *                   &tmp[0, 0], &k_endog)
 *         for k in range(k_endog):
 */
    __pyx_t_73 = 0;
    __pyx_t_74 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":1902
 *         strmm("R", "L", "T", "N", &k_endog, &k_endog,
 *           &alpha, &backward_factors[0,0], &k_endog,
 *                   &tmp[0, 0], &k_endog)             # <<<<<<<<<<<<<<
 *         for k in range(k_endog):
 *             scopy(&k_endog, &tmp[k,0], &k_endog, &backwards[s*k_endog2 + k*k_endog], &inc)
 */
    __pyx_t_75 = 0;
    __pyx_t_76 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":1900
 *         #           &tmp[0, 0], &k_endog,
 *         #   &beta, &backwards[s * k_endog2], &k_endog)
 *         strmm("R", "L", "T", "N", &k_endog, &k_endog,             # <<<<<<<<<<<<<<
 *           &alpha, &backward_factors[0,0], &k_endog,
 *                   &tmp[0, 0], &k_endog)
 */
    __pyx_v_strmm(__pyx_k_R, __pyx_k_L, __pyx_k_T, __pyx_k_N, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_alpha), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_backward_factors.data) + __pyx_t_73)) ) + __pyx_t_74 * __pyx_v_backward_factors.strides[1]) )))), (&__pyx_v_k_endog), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_tmp.data) + __pyx_t_75)) ) + __pyx_t_76 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_k_endog));

    /* "statsmodels\tsa\statespace\_statespace.pyx":1903
 *           &alpha, &backward_factors[0,0], &k_endog,
 *                   &tmp[0, 0], &k_endog)
 *         for k in range(k_endog):             # <<<<<<<<<<<<<<
 *             scopy(&k_endog, &tmp[k,0], &k_endog, &backwards[s*k_endog2 + k*k_endog], &inc)
 * 
 */
    __pyx_t_51 = __pyx_v_k_endog;
    for (__pyx_t_77 = 0; __pyx_t_77 < __pyx_t_51; __pyx_t_77+=1) {
      __pyx_v_k = __pyx_t_77;

      /* "statsmodels\tsa\statespace\_statespace.pyx":1904
 *                   &tmp[0, 0], &k_endog)
 *         for k in range(k_endog):
 *             scopy(&k_endog, &tmp[k,0], &k_endog, &backwards[s*k_endog2 + k*k_endog], &inc)             # <<<<<<<<<<<<<<
 * 
 *         # Update the variance
 */
      __pyx_t_78 = __pyx_v_k;
      __pyx_t_79 = 0;
      __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_scopy((&__pyx_v_k_endog), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_tmp.data) + __pyx_t_78)) ) + __pyx_t_79 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_k_endog), (&(__pyx_v_backwards[((__pyx_v_s * __pyx_v_k_endog2) + (__pyx_v_k * __pyx_v_k_endog))])), (&__pyx_v_inc));
    }

    /* "statsmodels\tsa\statespace\_statespace.pyx":1913
 *         # tmpT = np.dot(backward_variance.T, forwards[:, s*k_endog:(s+1)*k_endog].T)
 *         sgemm("T", "T", &k_endog, &k_endog, &k_endog,
 *           &alpha, &backward_variance[0, 0], &k_endog,             # <<<<<<<<<<<<<<
 *                   &forwards[s * k_endog2], &k_endog,
 *           &beta, &tmp[0, 0], &k_endog)
 */
    __pyx_t_80 = 0;
    __pyx_t_81 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":1915
 *           &alpha, &backward_variance[0, 0], &k_endog,
 *                   &forwards[s * k_endog2], &k_endog,
 *           &beta, &tmp[0, 0], &k_endog)             # <<<<<<<<<<<<<<
 *         # autocovariances[:, (s+1)*k_endog:(s+2)*k_endog] = tmp.copy().T
 *         scopy(&k_endog2, &tmp[0, 0], &inc, &autocovariances[0, (s+1)*k_endog], &inc)
 */
    __pyx_t_82 = 0;
    __pyx_t_83 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":1912
 *         # tmp = np.dot(forwards[:, s*k_endog:(s+1)*k_endog], backward_variance)
 *         # tmpT = np.dot(backward_variance.T, forwards[:, s*k_endog:(s+1)*k_endog].T)
 *         sgemm("T", "T", &k_endog, &k_endog, &k_endog,             # <<<<<<<<<<<<<<
 *           &alpha, &backward_variance[0, 0], &k_endog,
 *                   &forwards[s * k_endog2], &k_endog,
 */
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_sgemm(__pyx_k_T, __pyx_k_T, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_alpha), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_backward_variance.data) + __pyx_t_80)) ) + __pyx_t_81 * __pyx_v_backward_variance.strides[1]) )))), (&__pyx_v_k_endog), (&(__pyx_v_forwards[(__pyx_v_s * __pyx_v_k_endog2)])), (&__pyx_v_k_endog), (&__pyx_v_beta), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_tmp.data) + __pyx_t_82)) ) + __pyx_t_83 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_k_endog));

    /* "statsmodels\tsa\statespace\_statespace.pyx":1917
 *           &beta, &tmp[0, 0], &k_endog)
 *         # autocovariances[:, (s+1)*k_endog:(s+2)*k_endog] = tmp.copy().T
 *         scopy(&k_endog2, &tmp[0, 0], &inc, &autocovariances[0, (s+1)*k_endog], &inc)             # <<<<<<<<<<<<<<
 * 
 *         # Create the remaining k = 1, ..., s matrices,
 */
    __pyx_t_84 = 0;
    __pyx_t_85 = 0;
    __pyx_t_86 = 0;
    __pyx_t_87 = ((__pyx_v_s + 1) * __pyx_v_k_endog);
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_scopy((&__pyx_v_k_endog2), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_tmp.data) + __pyx_t_84)) ) + __pyx_t_85 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_autocovariances.data) + __pyx_t_86)) ) + __pyx_t_87 * __pyx_v_autocovariances.strides[1]) )))), (&__pyx_v_inc));

    /* "statsmodels\tsa\statespace\_statespace.pyx":1921
 *         # Create the remaining k = 1, ..., s matrices,
 *         # only has an effect if s >= 1
 *         for k in range(s):             # <<<<<<<<<<<<<<
 *             # forwards[:, k*k_endog:(k+1)*k_endog] = (
 *             #     prev_forwards[:, k*k_endog:(k+1)*k_endog] -
 */
    __pyx_t_51 = __pyx_v_s;
    for (__pyx_t_77 = 0; __pyx_t_77 < __pyx_t_51; __pyx_t_77+=1) {
      __pyx_v_k = __pyx_t_77;

      /* "statsmodels\tsa\statespace\_statespace.pyx":1929
 *             #     )
 *             # )
 *             scopy(&k_endog2, &prev_forwards[k * k_endog2], &inc, &forwards[k * k_endog2], &inc)             # <<<<<<<<<<<<<<
 *             sgemm("N", "N", &k_endog, &k_endog, &k_endog,
 *               &gamma, &forwards[s * k_endog2], &k_endog,
 */
      __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_scopy((&__pyx_v_k_endog2), (&(__pyx_v_prev_forwards[(__pyx_v_k * __pyx_v_k_endog2)])), (&__pyx_v_inc), (&(__pyx_v_forwards[(__pyx_v_k * __pyx_v_k_endog2)])), (&__pyx_v_inc));

      /* "statsmodels\tsa\statespace\_statespace.pyx":1930
 *             # )
 *             scopy(&k_endog2, &prev_forwards[k * k_endog2], &inc, &forwards[k * k_endog2], &inc)
 *             sgemm("N", "N", &k_endog, &k_endog, &k_endog,             # <<<<<<<<<<<<<<
 *               &gamma, &forwards[s * k_endog2], &k_endog,
 *                       &prev_backwards[(s - k - 1) * k_endog2], &k_endog,
 */
      __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_sgemm(__pyx_k_N, __pyx_k_N, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_gamma), (&(__pyx_v_forwards[(__pyx_v_s * __pyx_v_k_endog2)])), (&__pyx_v_k_endog), (&(__pyx_v_prev_backwards[(((__pyx_v_s - __pyx_v_k) - 1) * __pyx_v_k_endog2)])), (&__pyx_v_k_endog), (&__pyx_v_alpha), (&(__pyx_v_forwards[(__pyx_v_k * __pyx_v_k_endog2)])), (&__pyx_v_k_endog));

      /* "statsmodels\tsa\statespace\_statespace.pyx":1942
 *             #     )
 *             # )
 *             scopy(&k_endog2, &prev_backwards[k * k_endog2], &inc, &backwards[k * k_endog2], &inc)             # <<<<<<<<<<<<<<
 *             sgemm("N", "N", &k_endog, &k_endog, &k_endog,
 *               &gamma, &backwards[s * k_endog2], &k_endog,
 */
      __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_scopy((&__pyx_v_k_endog2), (&(__pyx_v_prev_backwards[(__pyx_v_k * __pyx_v_k_endog2)])), (&__pyx_v_inc), (&(__pyx_v_backwards[(__pyx_v_k * __pyx_v_k_endog2)])), (&__pyx_v_inc));

      /* "statsmodels\tsa\statespace\_statespace.pyx":1943
 *             # )
 *             scopy(&k_endog2, &prev_backwards[k * k_endog2], &inc, &backwards[k * k_endog2], &inc)
 *             sgemm("N", "N", &k_endog, &k_endog, &k_endog,             # <<<<<<<<<<<<<<
 *               &gamma, &backwards[s * k_endog2], &k_endog,
 *                       &prev_forwards[(s - k - 1) * k_endog2], &k_endog,
 */
      __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_sgemm(__pyx_k_N, __pyx_k_N, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_gamma), (&(__pyx_v_backwards[(__pyx_v_s * __pyx_v_k_endog2)])), (&__pyx_v_k_endog), (&(__pyx_v_prev_forwards[(((__pyx_v_s - __pyx_v_k) - 1) * __pyx_v_k_endog2)])), (&__pyx_v_k_endog), (&__pyx_v_alpha), (&(__pyx_v_backwards[(__pyx_v_k * __pyx_v_k_endog2)])), (&__pyx_v_k_endog));

      /* "statsmodels\tsa\statespace\_statespace.pyx":1953
 *             # )
 *             sgemm("N", "T", &k_endog, &k_endog, &k_endog,
 *               &alpha, &autocovariances[0, (k+1)*k_endog], &k_endog,             # <<<<<<<<<<<<<<
 *                       &prev_forwards[(s - k - 1) * k_endog2], &k_endog,
 *               &alpha, &autocovariances[0, (s+1)*k_endog], &k_endog)
 */
      __pyx_t_88 = 0;
      __pyx_t_89 = ((__pyx_v_k + 1) * __pyx_v_k_endog);

      /* "statsmodels\tsa\statespace\_statespace.pyx":1955
 *               &alpha, &autocovariances[0, (k+1)*k_endog], &k_endog,
 *                       &prev_forwards[(s - k - 1) * k_endog2], &k_endog,
 *               &alpha, &autocovariances[0, (s+1)*k_endog], &k_endog)             # <<<<<<<<<<<<<<
 * 
 *         # Create forward and backwards variances
 */
      __pyx_t_90 = 0;
      __pyx_t_91 = ((__pyx_v_s + 1) * __pyx_v_k_endog);

      /* "statsmodels\tsa\statespace\_statespace.pyx":1952
 *             #     prev_forwards[:, (s-k-1)*k_endog:(s-k)*k_endog].T
 *             # )
 *             sgemm("N", "T", &k_endog, &k_endog, &k_endog,             # <<<<<<<<<<<<<<
 *               &alpha, &autocovariances[0, (k+1)*k_endog], &k_endog,
 *                       &prev_forwards[(s - k - 1) * k_endog2], &k_endog,
 */
      __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_sgemm(__pyx_k_N, __pyx_k_T, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_alpha), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_autocovariances.data) + __pyx_t_88)) ) + __pyx_t_89 * __pyx_v_autocovariances.strides[1]) )))), (&__pyx_v_k_endog), (&(__pyx_v_prev_forwards[(((__pyx_v_s - __pyx_v_k) - 1) * __pyx_v_k_endog2)])), (&__pyx_v_k_endog), (&__pyx_v_alpha), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_autocovariances.data) + __pyx_t_90)) ) + __pyx_t_91 * __pyx_v_autocovariances.strides[1]) )))), (&__pyx_v_k_endog));
    }

    /* "statsmodels\tsa\statespace\_statespace.pyx":1967
 *         sgemm("N", "N", &k_endog, &k_endog, &k_endog,
 *           &alpha, &backwards[s * k_endog2], &k_endog,
 *                   &forward_variance[0, 0], &k_endog,             # <<<<<<<<<<<<<<
 *           &beta, &tmp2[0, 0], &k_endog)
 *         sgemm("N", "T", &k_endog, &k_endog, &k_endog,
 */
    __pyx_t_92 = 0;
    __pyx_t_93 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":1968
 *           &alpha, &backwards[s * k_endog2], &k_endog,
 *                   &forward_variance[0, 0], &k_endog,
 *           &beta, &tmp2[0, 0], &k_endog)             # <<<<<<<<<<<<<<
 *         sgemm("N", "T", &k_endog, &k_endog, &k_endog,
 *           &gamma, &tmp2[0, 0], &k_endog,
 */
    __pyx_t_94 = 0;
    __pyx_t_95 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":1965
 *         #     )
 *         # )
 *         sgemm("N", "N", &k_endog, &k_endog, &k_endog,             # <<<<<<<<<<<<<<
 *           &alpha, &backwards[s * k_endog2], &k_endog,
 *                   &forward_variance[0, 0], &k_endog,
 */
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_sgemm(__pyx_k_N, __pyx_k_N, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_alpha), (&(__pyx_v_backwards[(__pyx_v_s * __pyx_v_k_endog2)])), (&__pyx_v_k_endog), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_forward_variance.data) + __pyx_t_92)) ) + __pyx_t_93 * __pyx_v_forward_variance.strides[1]) )))), (&__pyx_v_k_endog), (&__pyx_v_beta), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_tmp2.data) + __pyx_t_94)) ) + __pyx_t_95 * __pyx_v_tmp2.strides[1]) )))), (&__pyx_v_k_endog));

    /* "statsmodels\tsa\statespace\_statespace.pyx":1970
 *           &beta, &tmp2[0, 0], &k_endog)
 *         sgemm("N", "T", &k_endog, &k_endog, &k_endog,
 *           &gamma, &tmp2[0, 0], &k_endog,             # <<<<<<<<<<<<<<
 *                   &backwards[s * k_endog2], &k_endog,
 *           &alpha, &backward_variance[0, 0], &k_endog)
 */
    __pyx_t_96 = 0;
    __pyx_t_97 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":1972
 *           &gamma, &tmp2[0, 0], &k_endog,
 *                   &backwards[s * k_endog2], &k_endog,
 *           &alpha, &backward_variance[0, 0], &k_endog)             # <<<<<<<<<<<<<<
 *         # forward_variance = (
 *         #     forward_variance -
 */
    __pyx_t_98 = 0;
    __pyx_t_99 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":1969
 *                   &forward_variance[0, 0], &k_endog,
 *           &beta, &tmp2[0, 0], &k_endog)
 *         sgemm("N", "T", &k_endog, &k_endog, &k_endog,             # <<<<<<<<<<<<<<
 *           &gamma, &tmp2[0, 0], &k_endog,
 *                   &backwards[s * k_endog2], &k_endog,
 */
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_sgemm(__pyx_k_N, __pyx_k_T, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_gamma), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_tmp2.data) + __pyx_t_96)) ) + __pyx_t_97 * __pyx_v_tmp2.strides[1]) )))), (&__pyx_v_k_endog), (&(__pyx_v_backwards[(__pyx_v_s * __pyx_v_k_endog2)])), (&__pyx_v_k_endog), (&__pyx_v_alpha), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_backward_variance.data) + __pyx_t_98)) ) + __pyx_t_99 * __pyx_v_backward_variance.strides[1]) )))), (&__pyx_v_k_endog));

    /* "statsmodels\tsa\statespace\_statespace.pyx":1982
 *         # )
 *         sgemm("T", "T", &k_endog, &k_endog, &k_endog,
 *           &gamma, &tmp[0, 0], &k_endog,             # <<<<<<<<<<<<<<
 *                   &forwards[s * k_endog2], &k_endog,
 *           &alpha, &forward_variance[0, 0], &k_endog)
 */
    __pyx_t_100 = 0;
    __pyx_t_101 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":1984
 *           &gamma, &tmp[0, 0], &k_endog,
 *                   &forwards[s * k_endog2], &k_endog,
 *           &alpha, &forward_variance[0, 0], &k_endog)             # <<<<<<<<<<<<<<
 * 
 *         # Cholesky factors
 */
    __pyx_t_102 = 0;
    __pyx_t_103 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":1981
 *         #     np.dot(tmpT.T, forwards[:, s*k_endog:(s+1)*k_endog].T)
 *         # )
 *         sgemm("T", "T", &k_endog, &k_endog, &k_endog,             # <<<<<<<<<<<<<<
 *           &gamma, &tmp[0, 0], &k_endog,
 *                   &forwards[s * k_endog2], &k_endog,
 */
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_sgemm(__pyx_k_T, __pyx_k_T, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_gamma), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_tmp.data) + __pyx_t_100)) ) + __pyx_t_101 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_k_endog), (&(__pyx_v_forwards[(__pyx_v_s * __pyx_v_k_endog2)])), (&__pyx_v_k_endog), (&__pyx_v_alpha), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_forward_variance.data) + __pyx_t_102)) ) + __pyx_t_103 * __pyx_v_forward_variance.strides[1]) )))), (&__pyx_v_k_endog));

    /* "statsmodels\tsa\statespace\_statespace.pyx":1989
 *         # forward_factors = linalg.cholesky(forward_variance, lower=True)
 *         # backward_factors =  linalg.cholesky(backward_variance, lower=True)
 *         scopy(&k_endog2, &forward_variance[0,0], &inc, &forward_factors[0,0], &inc)             # <<<<<<<<<<<<<<
 *         spotrf("L", &k_endog, &forward_factors[0,0], &k_endog, &info)
 *         scopy(&k_endog2, &backward_variance[0,0], &inc, &backward_factors[0,0], &inc)
 */
    __pyx_t_104 = 0;
    __pyx_t_105 = 0;
    __pyx_t_106 = 0;
    __pyx_t_107 = 0;
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_scopy((&__pyx_v_k_endog2), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_forward_variance.data) + __pyx_t_104)) ) + __pyx_t_105 * __pyx_v_forward_variance.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_forward_factors.data) + __pyx_t_106)) ) + __pyx_t_107 * __pyx_v_forward_factors.strides[1]) )))), (&__pyx_v_inc));

    /* "statsmodels\tsa\statespace\_statespace.pyx":1990
 *         # backward_factors =  linalg.cholesky(backward_variance, lower=True)
 *         scopy(&k_endog2, &forward_variance[0,0], &inc, &forward_factors[0,0], &inc)
 *         spotrf("L", &k_endog, &forward_factors[0,0], &k_endog, &info)             # <<<<<<<<<<<<<<
 *         scopy(&k_endog2, &backward_variance[0,0], &inc, &backward_factors[0,0], &inc)
 *         spotrf("L", &k_endog, &backward_factors[0,0], &k_endog, &info)
 */
    __pyx_t_108 = 0;
    __pyx_t_109 = 0;
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_spotrf(__pyx_k_L, (&__pyx_v_k_endog), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_forward_factors.data) + __pyx_t_108)) ) + __pyx_t_109 * __pyx_v_forward_factors.strides[1]) )))), (&__pyx_v_k_endog), (&__pyx_v_info));

    /* "statsmodels\tsa\statespace\_statespace.pyx":1991
 *         scopy(&k_endog2, &forward_variance[0,0], &inc, &forward_factors[0,0], &inc)
 *         spotrf("L", &k_endog, &forward_factors[0,0], &k_endog, &info)
 *         scopy(&k_endog2, &backward_variance[0,0], &inc, &backward_factors[0,0], &inc)             # <<<<<<<<<<<<<<
 *         spotrf("L", &k_endog, &backward_factors[0,0], &k_endog, &info)
 * 
 */
    __pyx_t_110 = 0;
    __pyx_t_111 = 0;
    __pyx_t_112 = 0;
    __pyx_t_113 = 0;
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_scopy((&__pyx_v_k_endog2), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_backward_variance.data) + __pyx_t_110)) ) + __pyx_t_111 * __pyx_v_backward_variance.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_backward_factors.data) + __pyx_t_112)) ) + __pyx_t_113 * __pyx_v_backward_factors.strides[1]) )))), (&__pyx_v_inc));

    /* "statsmodels\tsa\statespace\_statespace.pyx":1992
 *         spotrf("L", &k_endog, &forward_factors[0,0], &k_endog, &info)
 *         scopy(&k_endog2, &backward_variance[0,0], &inc, &backward_factors[0,0], &inc)
 *         spotrf("L", &k_endog, &backward_factors[0,0], &k_endog, &info)             # <<<<<<<<<<<<<<
 * 
 * 
 */
    __pyx_t_114 = 0;
    __pyx_t_115 = 0;
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_spotrf(__pyx_k_L, (&__pyx_v_k_endog), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_backward_factors.data) + __pyx_t_114)) ) + __pyx_t_115 * __pyx_v_backward_factors.strides[1]) )))), (&__pyx_v_k_endog), (&__pyx_v_info));
  }

  /* "statsmodels\tsa\statespace\_statespace.pyx":1997
 *     # If we do not want to use the transformed variance, we need to
 *     # adjust the constrained matrices, as presented in Lemma 2.3, see above
 *     if not transform_variance:             # <<<<<<<<<<<<<<
 *         if order % 2 == 0:
 *             forwards = &forwards2[0,0]
 */
  __pyx_t_3 = ((!(__pyx_v_transform_variance != 0)) != 0);
  if (__pyx_t_3) {

    /* "statsmodels\tsa\statespace\_statespace.pyx":1998
 *     # adjust the constrained matrices, as presented in Lemma 2.3, see above
 *     if not transform_variance:
 *         if order % 2 == 0:             # <<<<<<<<<<<<<<
 *             forwards = &forwards2[0,0]
 *         else:
 */
    __pyx_t_3 = ((__Pyx_mod_long(__pyx_v_order, 2) == 0) != 0);
    if (__pyx_t_3) {

      /* "statsmodels\tsa\statespace\_statespace.pyx":1999
 *     if not transform_variance:
 *         if order % 2 == 0:
 *             forwards = &forwards2[0,0]             # <<<<<<<<<<<<<<
 *         else:
 *             forwards = &forwards1[0,0]
 */
      __pyx_t_116 = 0;
      __pyx_t_117 = 0;
      __pyx_v_forwards = (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_forwards2.data) + __pyx_t_116)) ) + __pyx_t_117 * __pyx_v_forwards2.strides[1]) ))));
      goto __pyx_L16;
    }
    /*else*/ {

      /* "statsmodels\tsa\statespace\_statespace.pyx":2001
 *             forwards = &forwards2[0,0]
 *         else:
 *             forwards = &forwards1[0,0]             # <<<<<<<<<<<<<<
 * 
 *         # Here, we need to construct T such that:
 */
      __pyx_t_118 = 0;
      __pyx_t_119 = 0;
      __pyx_v_forwards = (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_forwards1.data) + __pyx_t_118)) ) + __pyx_t_119 * __pyx_v_forwards1.strides[1]) ))));
    }
    __pyx_L16:;

    /* "statsmodels\tsa\statespace\_statespace.pyx":2012
 *         # initial_variance_factor = np.linalg.cholesky(initial_variance)
 *         # L'
 *         spotrf("U", &k_endog, &initial_variance[0,0], &k_endog, &info)             # <<<<<<<<<<<<<<
 *         # transformed_variance_factor = np.linalg.cholesky(variance)
 *         # M'
 */
    if (unlikely(!__pyx_v_initial_variance.memview)) { __Pyx_RaiseUnboundLocalError("initial_variance"); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 2012; __pyx_clineno = __LINE__; goto __pyx_L1_error;} }
    __pyx_t_120 = 0;
    __pyx_t_121 = 0;
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_spotrf(__pyx_k_U, (&__pyx_v_k_endog), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_initial_variance.data) + __pyx_t_120)) ) + __pyx_t_121 * __pyx_v_initial_variance.strides[1]) )))), (&__pyx_v_k_endog), (&__pyx_v_info));

    /* "statsmodels\tsa\statespace\_statespace.pyx":2015
 *         # transformed_variance_factor = np.linalg.cholesky(variance)
 *         # M'
 *         scopy(&k_endog2, &forward_variance[0,0], &inc, &tmp[0,0], &inc)             # <<<<<<<<<<<<<<
 *         spotrf("U", &k_endog, &tmp[0,0], &k_endog, &info)
 *         # spotri("L", &k_endog, &tmp[0,0], &k_endog, &info)
 */
    __pyx_t_122 = 0;
    __pyx_t_123 = 0;
    __pyx_t_124 = 0;
    __pyx_t_125 = 0;
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_scopy((&__pyx_v_k_endog2), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_forward_variance.data) + __pyx_t_122)) ) + __pyx_t_123 * __pyx_v_forward_variance.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_tmp.data) + __pyx_t_124)) ) + __pyx_t_125 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_inc));

    /* "statsmodels\tsa\statespace\_statespace.pyx":2016
 *         # M'
 *         scopy(&k_endog2, &forward_variance[0,0], &inc, &tmp[0,0], &inc)
 *         spotrf("U", &k_endog, &tmp[0,0], &k_endog, &info)             # <<<<<<<<<<<<<<
 *         # spotri("L", &k_endog, &tmp[0,0], &k_endog, &info)
 * 
 */
    __pyx_t_126 = 0;
    __pyx_t_127 = 0;
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_spotrf(__pyx_k_U, (&__pyx_v_k_endog), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_tmp.data) + __pyx_t_126)) ) + __pyx_t_127 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_k_endog), (&__pyx_v_info));

    /* "statsmodels\tsa\statespace\_statespace.pyx":2021
 *         # We need to zero out the lower triangle of L', because ?trtrs only
 *         # knows that M' is upper triangular
 *         for s in range(k_endog - 1):          # column             # <<<<<<<<<<<<<<
 *             for k in range(s+1, k_endog):     # row
 *                 initial_variance[k, s] = 0
 */
    __pyx_t_128 = (__pyx_v_k_endog - 1);
    for (__pyx_t_32 = 0; __pyx_t_32 < __pyx_t_128; __pyx_t_32+=1) {
      __pyx_v_s = __pyx_t_32;

      /* "statsmodels\tsa\statespace\_statespace.pyx":2022
 *         # knows that M' is upper triangular
 *         for s in range(k_endog - 1):          # column
 *             for k in range(s+1, k_endog):     # row             # <<<<<<<<<<<<<<
 *                 initial_variance[k, s] = 0
 * 
 */
      __pyx_t_33 = __pyx_v_k_endog;
      for (__pyx_t_51 = (__pyx_v_s + 1); __pyx_t_51 < __pyx_t_33; __pyx_t_51+=1) {
        __pyx_v_k = __pyx_t_51;

        /* "statsmodels\tsa\statespace\_statespace.pyx":2023
 *         for s in range(k_endog - 1):          # column
 *             for k in range(s+1, k_endog):     # row
 *                 initial_variance[k, s] = 0             # <<<<<<<<<<<<<<
 * 
 *         # Note that T is lower triangular
 */
        if (unlikely(!__pyx_v_initial_variance.memview)) { __Pyx_RaiseUnboundLocalError("initial_variance"); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 2023; __pyx_clineno = __LINE__; goto __pyx_L1_error;} }
        __pyx_t_77 = __pyx_v_k;
        __pyx_t_129 = __pyx_v_s;
        *((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_initial_variance.data) + __pyx_t_77)) ) + __pyx_t_129 * __pyx_v_initial_variance.strides[1]) )) = 0.0;
      }
    }

    /* "statsmodels\tsa\statespace\_statespace.pyx":2030
 *         # transform = np.dot(initial_variance_factor,
 *         #                    np.linalg.inv(transformed_variance_factor))
 *         strtrs("U", "N", "N", &k_endog, &k_endog, &tmp[0,0], &k_endog,             # <<<<<<<<<<<<<<
 *                                                            &initial_variance[0, 0], &k_endog, &info)
 *         # Now:
 */
    __pyx_t_130 = 0;
    __pyx_t_131 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":2031
 *         #                    np.linalg.inv(transformed_variance_factor))
 *         strtrs("U", "N", "N", &k_endog, &k_endog, &tmp[0,0], &k_endog,
 *                                                            &initial_variance[0, 0], &k_endog, &info)             # <<<<<<<<<<<<<<
 *         # Now:
 *         # initial_variance = T'
 */
    if (unlikely(!__pyx_v_initial_variance.memview)) { __Pyx_RaiseUnboundLocalError("initial_variance"); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 2031; __pyx_clineno = __LINE__; goto __pyx_L1_error;} }
    __pyx_t_132 = 0;
    __pyx_t_133 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":2030
 *         # transform = np.dot(initial_variance_factor,
 *         #                    np.linalg.inv(transformed_variance_factor))
 *         strtrs("U", "N", "N", &k_endog, &k_endog, &tmp[0,0], &k_endog,             # <<<<<<<<<<<<<<
 *                                                            &initial_variance[0, 0], &k_endog, &info)
 *         # Now:
 */
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_strtrs(__pyx_k_U, __pyx_k_N, __pyx_k_N, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_tmp.data) + __pyx_t_130)) ) + __pyx_t_131 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_k_endog), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_initial_variance.data) + __pyx_t_132)) ) + __pyx_t_133 * __pyx_v_initial_variance.strides[1]) )))), (&__pyx_v_k_endog), (&__pyx_v_info));

    /* "statsmodels\tsa\statespace\_statespace.pyx":2035
 *         # initial_variance = T'
 * 
 *         for s in range(order):             # <<<<<<<<<<<<<<
 *             # forwards[:, s*k_endog:(s+1)*k_endog] = (
 *             #     np.dot(
 */
    __pyx_t_32 = __pyx_v_order;
    for (__pyx_t_33 = 0; __pyx_t_33 < __pyx_t_32; __pyx_t_33+=1) {
      __pyx_v_s = __pyx_t_33;

      /* "statsmodels\tsa\statespace\_statespace.pyx":2047
 * 
 *             # Get TF
 *             scopy(&k_endog2, &forwards[s * k_endog2], &inc, &tmp2[0,0], &inc)             # <<<<<<<<<<<<<<
 *             strmm("L", "U", "T", "N", &k_endog, &k_endog,
 *               &alpha, &initial_variance[0, 0], &k_endog,
 */
      __pyx_t_134 = 0;
      __pyx_t_135 = 0;
      __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_scopy((&__pyx_v_k_endog2), (&(__pyx_v_forwards[(__pyx_v_s * __pyx_v_k_endog2)])), (&__pyx_v_inc), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_tmp2.data) + __pyx_t_134)) ) + __pyx_t_135 * __pyx_v_tmp2.strides[1]) )))), (&__pyx_v_inc));

      /* "statsmodels\tsa\statespace\_statespace.pyx":2049
 *             scopy(&k_endog2, &forwards[s * k_endog2], &inc, &tmp2[0,0], &inc)
 *             strmm("L", "U", "T", "N", &k_endog, &k_endog,
 *               &alpha, &initial_variance[0, 0], &k_endog,             # <<<<<<<<<<<<<<
 *                       &tmp2[0, 0], &k_endog)
 *             for k in range(k_endog):
 */
      if (unlikely(!__pyx_v_initial_variance.memview)) { __Pyx_RaiseUnboundLocalError("initial_variance"); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 2049; __pyx_clineno = __LINE__; goto __pyx_L1_error;} }
      __pyx_t_136 = 0;
      __pyx_t_137 = 0;

      /* "statsmodels\tsa\statespace\_statespace.pyx":2050
 *             strmm("L", "U", "T", "N", &k_endog, &k_endog,
 *               &alpha, &initial_variance[0, 0], &k_endog,
 *                       &tmp2[0, 0], &k_endog)             # <<<<<<<<<<<<<<
 *             for k in range(k_endog):
 *                 scopy(&k_endog, &tmp2[k,0], &k_endog, &tmp[0, k], &inc)
 */
      __pyx_t_138 = 0;
      __pyx_t_139 = 0;

      /* "statsmodels\tsa\statespace\_statespace.pyx":2048
 *             # Get TF
 *             scopy(&k_endog2, &forwards[s * k_endog2], &inc, &tmp2[0,0], &inc)
 *             strmm("L", "U", "T", "N", &k_endog, &k_endog,             # <<<<<<<<<<<<<<
 *               &alpha, &initial_variance[0, 0], &k_endog,
 *                       &tmp2[0, 0], &k_endog)
 */
      __pyx_v_strmm(__pyx_k_L, __pyx_k_U, __pyx_k_T, __pyx_k_N, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_alpha), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_initial_variance.data) + __pyx_t_136)) ) + __pyx_t_137 * __pyx_v_initial_variance.strides[1]) )))), (&__pyx_v_k_endog), (&(*((__pyx_t_5numpy_float32_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float32_t *) __pyx_v_tmp2.data) + __pyx_t_138)) ) + __pyx_t_139 * __pyx_v_tmp2.strides[1]) )))), (&__pyx_v_k_endog));

      /* "statsmodels\tsa\statespace\_statespace.pyx":2051
 *               &alpha, &initial_variance[0, 0], &k_endog,
 *                       &tmp2[0, 0], &k_endog)
 *             for k in range(k_endog):             # <<<<<<<<<<<<<<
 *                 scopy(&k_endog, &tmp2[k,0], &k_endog, &tmp[0, k], &inc)
 *             # Get x'
 */
      __pyx_t_51 = __pyx_v_k_endog;
      for (__pyx_t_140 = 0; __pyx_t_140 < __pyx_t_51; __pyx_t_140+=1) {
        __pyx_v_k = __pyx_t_140;

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static int __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_zselect_state_cov(int __pyx_v_k_states, int __pyx_v_k_posdef, __pyx_t_double_complex *__pyx_v_tmp, __pyx_t_double_complex *__pyx_v_selection, __pyx_t_double_complex *__pyx_v_state_cov, __pyx_t_double_complex *__pyx_v_selected_state_cov) {
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 *     cdef:
 *         np.complex128_t alpha = 1.0             # <<<<<<<<<<<<<<
 *         np.complex128_t beta = 0.0
 * 
 */
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  /* "statsmodels\tsa\statespace\_statespace.pyx":2353
 *     cdef:
 *         np.complex128_t alpha = 1.0
 *         np.complex128_t beta = 0.0             # <<<<<<<<<<<<<<
 * 
 *     # Only need to do something if there is a state covariance matrix
 */
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  /* "statsmodels\tsa\statespace\_statespace.pyx":2357
 *     # Only need to do something if there is a state covariance matrix
 *     # (i.e k_posdof == 0)
 *     if k_posdef > 0:             # <<<<<<<<<<<<<<
 * 
 *         # #### Calculate selected state covariance matrix
 */
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 *         # $\\#_0 = 1.0 * R_t Q_t$
 *         # $(m \times r) = (m \times r) (r \times r)$
 *         zgemm("N", "N", &k_states, &k_posdef, &k_posdef,             # <<<<<<<<<<<<<<
 *               &alpha, selection, &k_states,
 *                       state_cov, &k_posdef,
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 *         # $Q_t^* = 1.0 * \\#_0 R_t'$
 *         # $(m \times m) = (m \times r) (m \times r)'$
 *         zgemm("N", "T", &k_states, &k_states, &k_posdef,             # <<<<<<<<<<<<<<
 *               &alpha, tmp, &k_states,
 *                       selection, &k_states,
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  /* "statsmodels\tsa\statespace\_statespace.pyx":2346
 * 
 * # ### Selected state covariance matrice
 * cdef int zselect_state_cov(int k_states, int k_posdef,             # <<<<<<<<<<<<<<
 *                                     np.complex128_t * tmp,
 *                                     np.complex128_t * selection,
 */

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/* "statsmodels\tsa\statespace\_statespace.pyx":2422
 * # is defined to be zero.
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 * cdef int zforecast_missing_conventional(zKalmanFilter kfilter):             # <<<<<<<<<<<<<<
 *     cdef int i, j
 *     cdef int inc = 1
 */

static int __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_zforecast_missing_conventional(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_kfilter) {
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  /* "statsmodels\tsa\statespace\_statespace.pyx":2424
 * cdef int zforecast_missing_conventional(zKalmanFilter kfilter):
 *     cdef int i, j
 *     cdef int inc = 1             # <<<<<<<<<<<<<<
 * 
 *     # #### Forecast for time t
 */
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  /* "statsmodels\tsa\statespace\_statespace.pyx":2433
 *     # #### Forecast error for time t
 *     # It is undefined here, since obs is nan
 *     for i in range(kfilter.k_endog):             # <<<<<<<<<<<<<<
 *         kfilter._forecast[i] = 0
 *         kfilter._forecast_error[i] = 0
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    /* "statsmodels\tsa\statespace\_statespace.pyx":2434
 *     # It is undefined here, since obs is nan
 *     for i in range(kfilter.k_endog):
 *         kfilter._forecast[i] = 0             # <<<<<<<<<<<<<<
 *         kfilter._forecast_error[i] = 0
 * 
 */
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    /* "statsmodels\tsa\statespace\_statespace.pyx":2435
 *     for i in range(kfilter.k_endog):
 *         kfilter._forecast[i] = 0
 *         kfilter._forecast_error[i] = 0             # <<<<<<<<<<<<<<
 * 
 *     # #### Forecast error covariance matrix for time t
 */
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 *     # #### Forecast error covariance matrix for time t
 *     # $F_t \equiv 0$
 *     for i in range(kfilter.k_endog):             # <<<<<<<<<<<<<<
 *         for j in range(kfilter.k_endog):
 *             kfilter._forecast_error_cov[j + i*kfilter.k_endog] = 0
 */
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    /* "statsmodels\tsa\statespace\_statespace.pyx":2440
 *     # $F_t \equiv 0$
 *     for i in range(kfilter.k_endog):
 *         for j in range(kfilter.k_endog):             # <<<<<<<<<<<<<<
 *             kfilter._forecast_error_cov[j + i*kfilter.k_endog] = 0
 * 
 */
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      /* "statsmodels\tsa\statespace\_statespace.pyx":2441
 *     for i in range(kfilter.k_endog):
 *         for j in range(kfilter.k_endog):
 *             kfilter._forecast_error_cov[j + i*kfilter.k_endog] = 0             # <<<<<<<<<<<<<<
 * 
 * cdef int zupdating_missing_conventional(zKalmanFilter kfilter):
 */
      (__pyx_v_kfilter->_forecast_error_cov[(__pyx_v_j + (__pyx_v_i * __pyx_v_kfilter->k_endog))]) = __pyx_t_double_complex_from_parts(0, 0);
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  /* "statsmodels\tsa\statespace\_statespace.pyx":2422
 * # is defined to be zero.
 * 
 * cdef int zforecast_missing_conventional(zKalmanFilter kfilter):             # <<<<<<<<<<<<<<
 *     cdef int i, j
 *     cdef int inc = 1
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/* "statsmodels\tsa\statespace\_statespace.pyx":2443
 *             kfilter._forecast_error_cov[j + i*kfilter.k_endog] = 0
 * 
 * cdef int zupdating_missing_conventional(zKalmanFilter kfilter):             # <<<<<<<<<<<<<<
 *     cdef int inc = 1
 * 
 */

static int __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_zupdating_missing_conventional(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_kfilter) {
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  /* "statsmodels\tsa\statespace\_statespace.pyx":2444
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 * cdef int zupdating_missing_conventional(zKalmanFilter kfilter):
 *     cdef int inc = 1             # <<<<<<<<<<<<<<
 * 
 *     # Simply copy over the input arrays ($a_t, P_t$) to the filtered arrays
 */
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 *     # Simply copy over the input arrays ($a_t, P_t$) to the filtered arrays
 *     # ($a_{t|t}, P_{t|t}$)
 *     zcopy(&kfilter.k_states, kfilter._input_state, &inc, kfilter._filtered_state, &inc)             # <<<<<<<<<<<<<<
 *     zcopy(&kfilter.k_states2, kfilter._input_state_cov, &inc, kfilter._filtered_state_cov, &inc)
 * 
 */
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  /* "statsmodels\tsa\statespace\_statespace.pyx":2449
 *     # ($a_{t|t}, P_{t|t}$)
 *     zcopy(&kfilter.k_states, kfilter._input_state, &inc, kfilter._filtered_state, &inc)
 *     zcopy(&kfilter.k_states2, kfilter._input_state_cov, &inc, kfilter._filtered_state_cov, &inc)             # <<<<<<<<<<<<<<
 * 
 * cdef np.complex128_t zinverse_missing_conventional(zKalmanFilter kfilter, np.complex128_t determinant)  except *:
 */
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  /* "statsmodels\tsa\statespace\_statespace.pyx":2443
 *             kfilter._forecast_error_cov[j + i*kfilter.k_endog] = 0
 * 
 * cdef int zupdating_missing_conventional(zKalmanFilter kfilter):             # <<<<<<<<<<<<<<
 *     cdef int inc = 1
 * 
 */

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/* "statsmodels\tsa\statespace\_statespace.pyx":2451
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 * 
 * cdef np.complex128_t zinverse_missing_conventional(zKalmanFilter kfilter, np.complex128_t determinant)  except *:             # <<<<<<<<<<<<<<
 *     # Since the inverse of the forecast error covariance matrix is not
 *     # stored, we don't need to fill it (e.g. with NPY_NAN values). Instead,
 */

static __pyx_t_double_complex __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_zinverse_missing_conventional(CYTHON_UNUSED struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_kfilter, CYTHON_UNUSED __pyx_t_double_complex __pyx_v_determinant) {
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 *     # just do a noop here and return a zero determinant ($|0|$).
 *     return 0.0             # <<<<<<<<<<<<<<
 * 
 * cdef np.complex128_t zloglikelihood_missing_conventional(zKalmanFilter kfilter, np.complex128_t determinant):
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 *     zcopy(&kfilter.k_states2, kfilter._input_state_cov, &inc, kfilter._filtered_state_cov, &inc)
 * 
 * cdef np.complex128_t zinverse_missing_conventional(zKalmanFilter kfilter, np.complex128_t determinant)  except *:             # <<<<<<<<<<<<<<
 *     # Since the inverse of the forecast error covariance matrix is not
 *     # stored, we don't need to fill it (e.g. with NPY_NAN values). Instead,
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/* "statsmodels\tsa\statespace\_statespace.pyx":2457
 *     return 0.0
 * 
 * cdef np.complex128_t zloglikelihood_missing_conventional(zKalmanFilter kfilter, np.complex128_t determinant):             # <<<<<<<<<<<<<<
 *     return 0.0
 * 
 */

static __pyx_t_double_complex __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_zloglikelihood_missing_conventional(CYTHON_UNUSED struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_kfilter, CYTHON_UNUSED __pyx_t_double_complex __pyx_v_determinant) {
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 * cdef np.complex128_t zloglikelihood_missing_conventional(zKalmanFilter kfilter, np.complex128_t determinant):
 *     return 0.0             # <<<<<<<<<<<<<<
 * 
 * # ### Conventional Kalman filter
 */
  __pyx_r = __pyx_t_double_complex_from_parts(0.0, 0);
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  /* "statsmodels\tsa\statespace\_statespace.pyx":2457
 *     return 0.0
 * 
 * cdef np.complex128_t zloglikelihood_missing_conventional(zKalmanFilter kfilter, np.complex128_t determinant):             # <<<<<<<<<<<<<<
 *     return 0.0
 * 
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/* "statsmodels\tsa\statespace\_statespace.pyx":2467
 * # See Durbin and Koopman (2012) Chapter 4
 * 
 * cdef int zforecast_conventional(zKalmanFilter kfilter):             # <<<<<<<<<<<<<<
 * 
 *     # Constants
 */

static int __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_zforecast_conventional(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_kfilter) {
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 *     # Constants
 *     cdef:
 *         int inc = 1, ld             # <<<<<<<<<<<<<<
 *         np.complex128_t alpha = 1.0
 *         np.complex128_t beta = 0.0
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 *     cdef:
 *         int inc = 1, ld
 *         np.complex128_t alpha = 1.0             # <<<<<<<<<<<<<<
 *         np.complex128_t beta = 0.0
 *         np.complex128_t gamma = -1.0
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  /* "statsmodels\tsa\statespace\_statespace.pyx":2473
 *         int inc = 1, ld
 *         np.complex128_t alpha = 1.0
 *         np.complex128_t beta = 0.0             # <<<<<<<<<<<<<<
 *         np.complex128_t gamma = -1.0
 * 
 */
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  /* "statsmodels\tsa\statespace\_statespace.pyx":2474
 *         np.complex128_t alpha = 1.0
 *         np.complex128_t beta = 0.0
 *         np.complex128_t gamma = -1.0             # <<<<<<<<<<<<<<
 * 
 *     # #### Forecast for time t
 */
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  /* "statsmodels\tsa\statespace\_statespace.pyx":2483
 * 
 *     # $\\# = d_t$
 *     zcopy(&kfilter.k_endog, kfilter._obs_intercept, &inc, kfilter._forecast, &inc)             # <<<<<<<<<<<<<<
 *     # `forecast` $= 1.0 * Z_t a_t + 1.0 * \\#$
 *     # $(p \times 1) = (p \times m) (m \times 1) + (p \times 1)$
 */
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  /* "statsmodels\tsa\statespace\_statespace.pyx":2486
 *     # `forecast` $= 1.0 * Z_t a_t + 1.0 * \\#$
 *     # $(p \times 1) = (p \times m) (m \times 1) + (p \times 1)$
 *     zgemv("N", &kfilter.k_endog, &kfilter.k_states,             # <<<<<<<<<<<<<<
 *           &alpha, kfilter._design, &kfilter.k_endog,
 *                   kfilter._input_state, &inc,
 */
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  /* "statsmodels\tsa\statespace\_statespace.pyx":2495
 * 
 *     # $\\# = y_t$
 *     zcopy(&kfilter.k_endog, kfilter._obs, &inc, kfilter._forecast_error, &inc)             # <<<<<<<<<<<<<<
 *     # $v_t = -1.0 * $ `forecast` $ + \\#$
 *     # $(p \times 1) = (p \times 1) + (p \times 1)$
 */
  __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zcopy((&__pyx_v_kfilter->k_endog), __pyx_v_kfilter->_obs, (&__pyx_v_inc), __pyx_v_kfilter->_forecast_error, (&__pyx_v_inc));

  /* "statsmodels\tsa\statespace\_statespace.pyx":2498
 *     # $v_t = -1.0 * $ `forecast` $ + \\#$
 *     # $(p \times 1) = (p \times 1) + (p \times 1)$
 *     zaxpy(&kfilter.k_endog, &gamma, kfilter._forecast, &inc, kfilter._forecast_error, &inc)             # <<<<<<<<<<<<<<
 * 
 *     # *Intermediate calculation* (used just below and then once more)
 */
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  /* "statsmodels\tsa\statespace\_statespace.pyx":2504
 *     # $\\#_1 = P_t Z_t'$
 *     # $(m \times p) = (m \times m) (p \times m)'$
 *     zgemm("N", "T", &kfilter.k_states, &kfilter.k_endog, &kfilter.k_states,             # <<<<<<<<<<<<<<
 *           &alpha, kfilter._input_state_cov, &kfilter.k_states,
 *                   kfilter._design, &kfilter.k_endog,
 */
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  /* "statsmodels\tsa\statespace\_statespace.pyx":2514
 *     # *Note*: this and does nothing at all to `forecast_error_cov` if
 *     # converged == True
 *     if not kfilter.converged:             # <<<<<<<<<<<<<<
 *         # $\\# = H_t$
 *         zcopy(&kfilter.k_endog2, kfilter._obs_cov, &inc, kfilter._forecast_error_cov, &inc)
 */
  __pyx_t_1 = ((!(__pyx_v_kfilter->converged != 0)) != 0);
  if (__pyx_t_1) {

    /* "statsmodels\tsa\statespace\_statespace.pyx":2516
 *     if not kfilter.converged:
 *         # $\\# = H_t$
 *         zcopy(&kfilter.k_endog2, kfilter._obs_cov, &inc, kfilter._forecast_error_cov, &inc)             # <<<<<<<<<<<<<<
 * 
 *         # $F_t = 1.0 * Z_t \\#_1 + 1.0 * \\#$
 */
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zcopy((&__pyx_v_kfilter->k_endog2), __pyx_v_kfilter->_obs_cov, (&__pyx_v_inc), __pyx_v_kfilter->_forecast_error_cov, (&__pyx_v_inc));

    /* "statsmodels\tsa\statespace\_statespace.pyx":2519
 * 
 *         # $F_t = 1.0 * Z_t \\#_1 + 1.0 * \\#$
 *         zgemm("N", "N", &kfilter.k_endog, &kfilter.k_endog, &kfilter.k_states,             # <<<<<<<<<<<<<<
 *               &alpha, kfilter._design, &kfilter.k_endog,
 *                      kfilter._tmp1, &kfilter.k_states,
 */
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zgemm(__pyx_k_N, __pyx_k_N, (&__pyx_v_kfilter->k_endog), (&__pyx_v_kfilter->k_endog), (&__pyx_v_kfilter->k_states), (&__pyx_v_alpha), __pyx_v_kfilter->_design, (&__pyx_v_kfilter->k_endog), __pyx_v_kfilter->_tmp1, (&__pyx_v_kfilter->k_states), (&__pyx_v_alpha), __pyx_v_kfilter->_forecast_error_cov, (&__pyx_v_kfilter->k_endog));
    goto __pyx_L3;
  }
  __pyx_L3:;

  /* "statsmodels\tsa\statespace\_statespace.pyx":2524
 *               &alpha, kfilter._forecast_error_cov, &kfilter.k_endog)
 * 
 *     return 0             # <<<<<<<<<<<<<<
 * 
 * cdef int zupdating_conventional(zKalmanFilter kfilter):
 */
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 * cdef int zforecast_conventional(zKalmanFilter kfilter):             # <<<<<<<<<<<<<<
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 * cdef int zupdating_conventional(zKalmanFilter kfilter):             # <<<<<<<<<<<<<<
 *     # Constants
 *     cdef:
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 *         np.complex128_t beta = 0.0             # <<<<<<<<<<<<<<
 *         np.complex128_t gamma = -1.0
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 */
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 *         np.complex128_t alpha = 1.0
 *         np.complex128_t beta = 0.0
 *         np.complex128_t gamma = -1.0             # <<<<<<<<<<<<<<
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 *         # $(m \times m) = (m \times p) (p \times m)$
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 *         # $(m \times m) = (m \times m) (m \times m) + (m \times m)$
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 * cdef int zprediction_conventional(zKalmanFilter kfilter):
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 * cdef int zupdating_conventional(zKalmanFilter kfilter):             # <<<<<<<<<<<<<<
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/* "statsmodels\tsa\statespace\_statespace.pyx":2569
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 *     # Constants
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 *         np.complex128_t beta = 0.0
 *         np.complex128_t gamma = -1.0             # <<<<<<<<<<<<<<
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 *     zcopy(&kfilter.k_states, kfilter._state_intercept, &inc, kfilter._predicted_state, &inc)
 *     zgemv("N", &kfilter.k_states, &kfilter.k_states,             # <<<<<<<<<<<<<<
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  /* "statsmodels\tsa\statespace\_statespace.pyx":2591
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 *     # converged == True
 *     if not kfilter.converged:             # <<<<<<<<<<<<<<
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 *         # $(m \times m) = (m \times m) (m \times m)$
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 * 
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 * cdef int zprediction_conventional(zKalmanFilter kfilter):             # <<<<<<<<<<<<<<
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/* "statsmodels\tsa\statespace\_statespace.pyx":2612
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 *         np.complex128_t beta = 0.0             # <<<<<<<<<<<<<<
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 * 
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 *     """
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 *     if not kfilter.converged:
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 * 
 *     if not kfilter.converged:             # <<<<<<<<<<<<<<
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 *         # Continue taking the inverse
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 *         for i in range(kfilter.k_endog):             # <<<<<<<<<<<<<<
 *             for j in range(i):
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      /* "statsmodels\tsa\statespace\_statespace.pyx":2777
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 */
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        /* "statsmodels\tsa\statespace\_statespace.pyx":2778
 *         for i in range(kfilter.k_endog):
 *             for j in range(i):
 *                 kfilter._forecast_error_fac[i + j*kfilter.k_endog] = kfilter._forecast_error_fac[j + i*kfilter.k_endog]             # <<<<<<<<<<<<<<
 * 
 * 
 */
        (__pyx_v_kfilter->_forecast_error_fac[(__pyx_v_i + (__pyx_v_j * __pyx_v_kfilter->k_endog))]) = (__pyx_v_kfilter->_forecast_error_fac[(__pyx_v_j + (__pyx_v_i * __pyx_v_kfilter->k_endog))]);
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  /* "statsmodels\tsa\statespace\_statespace.pyx":2787
 *     #zsymv("U", &kfilter.k_endog, &alpha, kfilter._forecast_error_fac, &kfilter.k_endog,
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  /* "statsmodels\tsa\statespace\_statespace.pyx":2798
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 *                    &beta, kfilter._tmp3, &kfilter.k_endog)
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 *     return determinant             # <<<<<<<<<<<<<<
 * 
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/* "statsmodels\tsa\statespace\_statespace.pyx":2805
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 *     """
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 */

static __pyx_t_double_complex __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_zinverse_lu(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_kfilter, __pyx_t_double_complex __pyx_v_determinant) {
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 *         np.complex128_t beta = 0.0             # <<<<<<<<<<<<<<
 * 
 *     if not kfilter.converged:
 */
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  /* "statsmodels\tsa\statespace\_statespace.pyx":2818
 *         np.complex128_t beta = 0.0
 * 
 *     if not kfilter.converged:             # <<<<<<<<<<<<<<
 *         # Perform the Cholesky decomposition and get the determinant
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 *     if not kfilter.converged:
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 *         # Continue taking the inverse
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 * 
 *         # Continue taking the inverse
 *         zgetri(&kfilter.k_endog, kfilter._forecast_error_fac, &kfilter.k_endog,             # <<<<<<<<<<<<<<
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 * 
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/* "statsmodels\tsa\statespace\_statespace.pyx":2844
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static __pyx_t_double_complex __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_zsolve_cholesky(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_kfilter, __pyx_t_double_complex __pyx_v_determinant) {
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 *     if not kfilter.converged:
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 *     # Solve the linear systems
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  /* "statsmodels\tsa\statespace\_statespace.pyx":2862
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  /* "statsmodels\tsa\statespace\_statespace.pyx":2863
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 *     # `tmp3` array used here, dimension $(p \times m)$
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 *     # `tmp3` array used here, dimension $(p \times m)$
 *     # $F_t \\#_3 = Z_t$
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 *     zpotrs("U", &kfilter.k_endog, &kfilter.k_states, kfilter._forecast_error_fac, &kfilter.k_endog, kfilter._tmp3, &kfilter.k_endog, &info)
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 */
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 * 
 *     return determinant
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 * 
 *     return determinant             # <<<<<<<<<<<<<<
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 * 
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/* "statsmodels\tsa\statespace\_statespace.pyx":2872
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 * 
 * cdef np.complex128_t zsolve_lu(zKalmanFilter kfilter, np.complex128_t determinant) except *:             # <<<<<<<<<<<<<<
 *     """
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 *             int obs_intercept_t = 0             # <<<<<<<<<<<<<<
 *             int obs_cov_t = 0
 *             int transition_t = 0
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 *             int obs_intercept_t = 0
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 *             int transition_t = 0
 *             int state_intercept_t = 0
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 *             int obs_cov_t = 0
 *             int transition_t = 0             # <<<<<<<<<<<<<<
 *             int state_intercept_t = 0
 *             int selection_t = 0
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 *             int transition_t = 0
 *             int state_intercept_t = 0             # <<<<<<<<<<<<<<
 *             int selection_t = 0
 *             int state_cov_t = 0
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 *             int state_intercept_t = 0
 *             int selection_t = 0             # <<<<<<<<<<<<<<
 *             int state_cov_t = 0
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 */
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 *             int selection_t = 0
 *             int state_cov_t = 0             # <<<<<<<<<<<<<<
 * 
 *         # Get indices for possibly time-varying arrays
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 *             if self.model.obs_cov.shape[2] > 1:            obs_cov_t = t
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 *             if self.model.state_intercept.shape[1] > 1:    state_intercept_t = t
 *             if self.model.selection.shape[2] > 1:          selection_t = t
 *             if self.model.state_cov.shape[2] > 1:          state_cov_t = t             # <<<<<<<<<<<<<<
 * 
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 * 
 *         # Initialize object-level pointers to statespace arrays
 *         self._obs = &self.model.obs[0, t]             # <<<<<<<<<<<<<<
 *         self._design = &self.model.design[0, 0, design_t]
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 *         # Initialize object-level pointers to statespace arrays
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 *         self._design = &self.model.design[0, 0, design_t]             # <<<<<<<<<<<<<<
 *         self._obs_intercept = &self.model.obs_intercept[0, obs_intercept_t]
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 */
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 *         self._obs_intercept = &self.model.obs_intercept[0, obs_intercept_t]             # <<<<<<<<<<<<<<
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 *         self._transition = &self.model.transition[0, 0, transition_t]
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 *         self._obs_intercept = &self.model.obs_intercept[0, obs_intercept_t]
 *         self._obs_cov = &self.model.obs_cov[0, 0, obs_cov_t]             # <<<<<<<<<<<<<<
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      __pyx_t_5 = (__pyx_v_j + (__pyx_v_i * __pyx_v_self->model->k_endog));
      *((__pyx_t_double_complex *) ( /* dim=0 */ (__pyx_v_self->selected_design.data + __pyx_t_5 * __pyx_v_self->selected_design.strides[0]) )) = __pyx_t_double_complex_from_parts(0.0, 0);
    }
  }

  /* "statsmodels\tsa\statespace\_statespace.pyx":3520
 *             for j in range(self.model.k_endog):
 *                 self.selected_design[j + i*self.model.k_endog] = 0.0
 *         self._design = &self.selected_design[0]             # <<<<<<<<<<<<<<
 * 
 *         # Change the forecasting step to set the forecast at the intercept
 */
  if (unlikely(!__pyx_v_self->selected_design.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 3520; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
  __pyx_t_6 = 0;
  __pyx_v_self->_design = (&(*((__pyx_t_double_complex *) ( /* dim=0 */ (__pyx_v_self->selected_design.data + __pyx_t_6 * __pyx_v_self->selected_design.strides[0]) ))));

  /* "statsmodels\tsa\statespace\_statespace.pyx":3524
 *         # Change the forecasting step to set the forecast at the intercept
 *         # $d_t$, so that the forecast error is $v_t = y_t - d_t$.
 *         self.forecasting = zforecast_missing_conventional             # <<<<<<<<<<<<<<
 * 
 *         # Change the updating step to just copy $a_{t|t} = a_t$ and
 */
  __pyx_v_self->forecasting = __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_zforecast_missing_conventional;

  /* "statsmodels\tsa\statespace\_statespace.pyx":3528
 *         # Change the updating step to just copy $a_{t|t} = a_t$ and
 *         # $P_{t|t} = P_t$
 *         self.updating = zupdating_missing_conventional             # <<<<<<<<<<<<<<
 * 
 *         # Change the inversion step to inverse to nans.
 */
  __pyx_v_self->updating = __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_zupdating_missing_conventional;

  /* "statsmodels\tsa\statespace\_statespace.pyx":3531
 * 
 *         # Change the inversion step to inverse to nans.
 *         self.inversion = zinverse_missing_conventional             # <<<<<<<<<<<<<<
 * 
 *         # Change the loglikelihood calculation to give zero.
 */
  __pyx_v_self->inversion = __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_zinverse_missing_conventional;

  /* "statsmodels\tsa\statespace\_statespace.pyx":3534
 * 
 *         # Change the loglikelihood calculation to give zero.
 *         self.calculate_loglikelihood = zloglikelihood_missing_conventional             # <<<<<<<<<<<<<<
 * 
 *         # The prediction step is the same as the conventional Kalman
 */
  __pyx_v_self->calculate_loglikelihood = __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_zloglikelihood_missing_conventional;

  /* "statsmodels\tsa\statespace\_statespace.pyx":3503
 *             self.k_endogstates = self.k_endog * self.k_states
 * 
 *     cdef void _select_missing_entire_obs(self):             # <<<<<<<<<<<<<<
 *         cdef:
 *             int i, j
 */

  /* function exit code */
  goto __pyx_L0;
  __pyx_L1_error:;
  __Pyx_WriteUnraisable("statsmodels.tsa.statespace._statespace.zKalmanFilter._select_missing_entire_obs", __pyx_clineno, __pyx_lineno, __pyx_filename, 0);
  __pyx_L0:;
  __Pyx_RefNannyFinishContext();
}

/* "statsmodels\tsa\statespace\_statespace.pyx":3539
 *         # filter
 * 
 *     cdef void _select_missing_partial_obs(self):             # <<<<<<<<<<<<<<
 *         cdef:
 *             int i, j, k, l
 */

static void __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter__select_missing_partial_obs(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self) {
  int __pyx_v_i;
  int __pyx_v_j;
  int __pyx_v_k;
  int __pyx_v_l;
  CYTHON_UNUSED int __pyx_v_inc;
  int __pyx_v_design_t;
  int __pyx_v_obs_cov_t;
  __Pyx_RefNannyDeclarations
  int __pyx_t_1;
  int __pyx_t_2;
  int __pyx_t_3;
  int __pyx_t_4;
  int __pyx_t_5;
  int __pyx_t_6;
  int __pyx_t_7;
  int __pyx_t_8;
  int __pyx_t_9;
  int __pyx_t_10;
  Py_ssize_t __pyx_t_11;
  int __pyx_t_12;
  int __pyx_t_13;
  int __pyx_t_14;
  int __pyx_t_15;
  int __pyx_t_16;
  int __pyx_t_17;
  int __pyx_t_18;
  int __pyx_t_19;
  int __pyx_t_20;
  int __pyx_t_21;
  Py_ssize_t __pyx_t_22;
  Py_ssize_t __pyx_t_23;
  Py_ssize_t __pyx_t_24;
  int __pyx_lineno = 0;
  const char *__pyx_filename = NULL;
  int __pyx_clineno = 0;
  __Pyx_RefNannySetupContext("_select_missing_partial_obs", 0);

  /* "statsmodels\tsa\statespace\_statespace.pyx":3542
 *         cdef:
 *             int i, j, k, l
 *             int inc = 1             # <<<<<<<<<<<<<<
 *             int design_t = 0
 *             int obs_cov_t = 0
 */
  __pyx_v_inc = 1;

  /* "statsmodels\tsa\statespace\_statespace.pyx":3543
 *             int i, j, k, l
 *             int inc = 1
 *             int design_t = 0             # <<<<<<<<<<<<<<
 *             int obs_cov_t = 0
 *         # Mark as not converged so that it does not inappropriately
 */
  __pyx_v_design_t = 0;

  /* "statsmodels\tsa\statespace\_statespace.pyx":3544
 *             int inc = 1
 *             int design_t = 0
 *             int obs_cov_t = 0             # <<<<<<<<<<<<<<
 *         # Mark as not converged so that it does not inappropriately
 *         # copy over steady state matrices
 */
  __pyx_v_obs_cov_t = 0;

  /* "statsmodels\tsa\statespace\_statespace.pyx":3547
 *         # Mark as not converged so that it does not inappropriately
 *         # copy over steady state matrices
 *         self.converged = 0             # <<<<<<<<<<<<<<
 * 
 *         # Set dimensions
 */
  __pyx_v_self->converged = 0;

  /* "statsmodels\tsa\statespace\_statespace.pyx":3550
 * 
 *         # Set dimensions
 *         self.k_endog = self.model.k_endog - self.model.nmissing[self.t]             # <<<<<<<<<<<<<<
 *         self.k_endog2 = self.k_endog**2
 *         self.k_endogstates = self.k_endog * self.k_states
 */
  if (unlikely(!__pyx_v_self->model->nmissing.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 3550; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
  __pyx_t_1 = __pyx_v_self->t;
  __pyx_v_self->k_endog = (__pyx_v_self->model->k_endog - (*((int *) ( /* dim=0 */ (__pyx_v_self->model->nmissing.data + __pyx_t_1 * __pyx_v_self->model->nmissing.strides[0]) ))));

  /* "statsmodels\tsa\statespace\_statespace.pyx":3551
 *         # Set dimensions
 *         self.k_endog = self.model.k_endog - self.model.nmissing[self.t]
 *         self.k_endog2 = self.k_endog**2             # <<<<<<<<<<<<<<
 *         self.k_endogstates = self.k_endog * self.k_states
 * 
 */
  __pyx_v_self->k_endog2 = __Pyx_pow_long(((long)__pyx_v_self->k_endog), 2);

  /* "statsmodels\tsa\statespace\_statespace.pyx":3552
 *         self.k_endog = self.model.k_endog - self.model.nmissing[self.t]
 *         self.k_endog2 = self.k_endog**2
 *         self.k_endogstates = self.k_endog * self.k_states             # <<<<<<<<<<<<<<
 * 
 *         if self.model.design.shape[2] > 1: design_t = self.t
 */
  __pyx_v_self->k_endogstates = (__pyx_v_self->k_endog * __pyx_v_self->k_states);

  /* "statsmodels\tsa\statespace\_statespace.pyx":3554
 *         self.k_endogstates = self.k_endog * self.k_states
 * 
 *         if self.model.design.shape[2] > 1: design_t = self.t             # <<<<<<<<<<<<<<
 *         if self.model.obs_cov.shape[2] > 1: obs_cov_t = self.t
 * 
 */
  if (unlikely(!__pyx_v_self->model->design.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 3554; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
  __pyx_t_2 = (((__pyx_v_self->model->design.shape[2]) > 1) != 0);
  if (__pyx_t_2) {
    __pyx_t_3 = __pyx_v_self->t;
    __pyx_v_design_t = __pyx_t_3;
    goto __pyx_L3;
  }
  __pyx_L3:;

  /* "statsmodels\tsa\statespace\_statespace.pyx":3555
 * 
 *         if self.model.design.shape[2] > 1: design_t = self.t
 *         if self.model.obs_cov.shape[2] > 1: obs_cov_t = self.t             # <<<<<<<<<<<<<<
 * 
 *         k = 0
 */
  if (unlikely(!__pyx_v_self->model->obs_cov.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 3555; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
  __pyx_t_2 = (((__pyx_v_self->model->obs_cov.shape[2]) > 1) != 0);
  if (__pyx_t_2) {
    __pyx_t_3 = __pyx_v_self->t;
    __pyx_v_obs_cov_t = __pyx_t_3;
    goto __pyx_L4;
  }
  __pyx_L4:;

  /* "statsmodels\tsa\statespace\_statespace.pyx":3557
 *         if self.model.obs_cov.shape[2] > 1: obs_cov_t = self.t
 * 
 *         k = 0             # <<<<<<<<<<<<<<
 *         for i in range(self.model.k_endog):
 *             if not self.model.missing[i, self.t]:
 */
  __pyx_v_k = 0;

  /* "statsmodels\tsa\statespace\_statespace.pyx":3558
 * 
 *         k = 0
 *         for i in range(self.model.k_endog):             # <<<<<<<<<<<<<<
 *             if not self.model.missing[i, self.t]:
 * 
 */
  __pyx_t_3 = __pyx_v_self->model->k_endog;
  for (__pyx_t_4 = 0; __pyx_t_4 < __pyx_t_3; __pyx_t_4+=1) {
    __pyx_v_i = __pyx_t_4;

    /* "statsmodels\tsa\statespace\_statespace.pyx":3559
 *         k = 0
 *         for i in range(self.model.k_endog):
 *             if not self.model.missing[i, self.t]:             # <<<<<<<<<<<<<<
 * 
 *                 self.selected_obs[k] = self.model.obs[i, self.t]
 */
    if (unlikely(!__pyx_v_self->model->missing.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 3559; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
    __pyx_t_5 = __pyx_v_i;
    __pyx_t_6 = __pyx_v_self->t;
    __pyx_t_2 = ((!((*((int *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((int *) __pyx_v_self->model->missing.data) + __pyx_t_5)) ) + __pyx_t_6 * __pyx_v_self->model->missing.strides[1]) ))) != 0)) != 0);
    if (__pyx_t_2) {

      /* "statsmodels\tsa\statespace\_statespace.pyx":3561
 *             if not self.model.missing[i, self.t]:
 * 
 *                 self.selected_obs[k] = self.model.obs[i, self.t]             # <<<<<<<<<<<<<<
 * 
 *                 # i is rows
 */
      if (unlikely(!__pyx_v_self->model->obs.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 3561; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
      __pyx_t_7 = __pyx_v_i;
      __pyx_t_8 = __pyx_v_self->t;
      if (unlikely(!__pyx_v_self->selected_obs.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 3561; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
      __pyx_t_9 = __pyx_v_k;
      *((__pyx_t_double_complex *) ( /* dim=0 */ (__pyx_v_self->selected_obs.data + __pyx_t_9 * __pyx_v_self->selected_obs.strides[0]) )) = (*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_self->model->obs.data) + __pyx_t_7)) ) + __pyx_t_8 * __pyx_v_self->model->obs.strides[1]) )));

      /* "statsmodels\tsa\statespace\_statespace.pyx":3566
 *                 # k is rows
 *                 zcopy(&self.model.k_states,
 *                       &self.model.design[i, 0, design_t], &self.model.k_endog,             # <<<<<<<<<<<<<<
 *                       &self.selected_design[k], &self.k_endog)
 * 
 */
      if (unlikely(!__pyx_v_self->model->design.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 3566; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
      __pyx_t_10 = __pyx_v_i;
      __pyx_t_11 = 0;
      __pyx_t_12 = __pyx_v_design_t;

      /* "statsmodels\tsa\statespace\_statespace.pyx":3567
 *                 zcopy(&self.model.k_states,
 *                       &self.model.design[i, 0, design_t], &self.model.k_endog,
 *                       &self.selected_design[k], &self.k_endog)             # <<<<<<<<<<<<<<
 * 
 *                 # i, k is columns
 */
      if (unlikely(!__pyx_v_self->selected_design.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 3567; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
      __pyx_t_13 = __pyx_v_k;

      /* "statsmodels\tsa\statespace\_statespace.pyx":3565
 *                 # i is rows
 *                 # k is rows
 *                 zcopy(&self.model.k_states,             # <<<<<<<<<<<<<<
 *                       &self.model.design[i, 0, design_t], &self.model.k_endog,
 *                       &self.selected_design[k], &self.k_endog)
 */
      __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zcopy((&__pyx_v_self->model->k_states), (&(*((__pyx_t_double_complex *) ( /* dim=2 */ (( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_self->model->design.data) + __pyx_t_10)) ) + __pyx_t_11 * __pyx_v_self->model->design.strides[1]) ) + __pyx_t_12 * __pyx_v_self->model->design.strides[2]) )))), (&__pyx_v_self->model->k_endog), (&(*((__pyx_t_double_complex *) ( /* dim=0 */ (__pyx_v_self->selected_design.data + __pyx_t_13 * __pyx_v_self->selected_design.strides[0]) )))), (&__pyx_v_self->k_endog));

      /* "statsmodels\tsa\statespace\_statespace.pyx":3571
 *                 # i, k is columns
 *                 # j, l is rows
 *                 l = 0             # <<<<<<<<<<<<<<
 *                 for j in range(self.model.k_endog):
 *                     if not self.model.missing[j, self.t]:
 */
      __pyx_v_l = 0;

      /* "statsmodels\tsa\statespace\_statespace.pyx":3572
 *                 # j, l is rows
 *                 l = 0
 *                 for j in range(self.model.k_endog):             # <<<<<<<<<<<<<<
 *                     if not self.model.missing[j, self.t]:
 *                         self.selected_obs_cov[l + k*self.k_endog] = self.model.obs_cov[j, i, obs_cov_t]
 */
      __pyx_t_14 = __pyx_v_self->model->k_endog;
      for (__pyx_t_15 = 0; __pyx_t_15 < __pyx_t_14; __pyx_t_15+=1) {
        __pyx_v_j = __pyx_t_15;

        /* "statsmodels\tsa\statespace\_statespace.pyx":3573
 *                 l = 0
 *                 for j in range(self.model.k_endog):
 *                     if not self.model.missing[j, self.t]:             # <<<<<<<<<<<<<<
 *                         self.selected_obs_cov[l + k*self.k_endog] = self.model.obs_cov[j, i, obs_cov_t]
 *                         l += 1
 */
        if (unlikely(!__pyx_v_self->model->missing.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 3573; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
        __pyx_t_16 = __pyx_v_j;
        __pyx_t_17 = __pyx_v_self->t;
        __pyx_t_2 = ((!((*((int *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((int *) __pyx_v_self->model->missing.data) + __pyx_t_16)) ) + __pyx_t_17 * __pyx_v_self->model->missing.strides[1]) ))) != 0)) != 0);
        if (__pyx_t_2) {

          /* "statsmodels\tsa\statespace\_statespace.pyx":3574
 *                 for j in range(self.model.k_endog):
 *                     if not self.model.missing[j, self.t]:
 *                         self.selected_obs_cov[l + k*self.k_endog] = self.model.obs_cov[j, i, obs_cov_t]             # <<<<<<<<<<<<<<
 *                         l += 1
 *                 k += 1
 */
          if (unlikely(!__pyx_v_self->model->obs_cov.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 3574; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
          __pyx_t_18 = __pyx_v_j;
          __pyx_t_19 = __pyx_v_i;
          __pyx_t_20 = __pyx_v_obs_cov_t;
          if (unlikely(!__pyx_v_self->selected_obs_cov.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 3574; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
          __pyx_t_21 = (__pyx_v_l + (__pyx_v_k * __pyx_v_self->k_endog));
          *((__pyx_t_double_complex *) ( /* dim=0 */ (__pyx_v_self->selected_obs_cov.data + __pyx_t_21 * __pyx_v_self->selected_obs_cov.strides[0]) )) = (*((__pyx_t_double_complex *) ( /* dim=2 */ (( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_self->model->obs_cov.data) + __pyx_t_18)) ) + __pyx_t_19 * __pyx_v_self->model->obs_cov.strides[1]) ) + __pyx_t_20 * __pyx_v_self->model->obs_cov.strides[2]) )));

          /* "statsmodels\tsa\statespace\_statespace.pyx":3575
 *                     if not self.model.missing[j, self.t]:
 *                         self.selected_obs_cov[l + k*self.k_endog] = self.model.obs_cov[j, i, obs_cov_t]
 *                         l += 1             # <<<<<<<<<<<<<<
 *                 k += 1
 *         self._obs = &self.selected_obs[0]
 */
          __pyx_v_l = (__pyx_v_l + 1);
          goto __pyx_L10;
        }
        __pyx_L10:;
      }

      /* "statsmodels\tsa\statespace\_statespace.pyx":3576
 *                         self.selected_obs_cov[l + k*self.k_endog] = self.model.obs_cov[j, i, obs_cov_t]
 *                         l += 1
 *                 k += 1             # <<<<<<<<<<<<<<
 *         self._obs = &self.selected_obs[0]
 *         self._design = &self.selected_design[0]
 */
      __pyx_v_k = (__pyx_v_k + 1);
      goto __pyx_L7;
    }
    __pyx_L7:;
  }

  /* "statsmodels\tsa\statespace\_statespace.pyx":3577
 *                         l += 1
 *                 k += 1
 *         self._obs = &self.selected_obs[0]             # <<<<<<<<<<<<<<
 *         self._design = &self.selected_design[0]
 *         self._obs_cov = &self.selected_obs_cov[0]
 */
  if (unlikely(!__pyx_v_self->selected_obs.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 3577; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
  __pyx_t_22 = 0;
  __pyx_v_self->_obs = (&(*((__pyx_t_double_complex *) ( /* dim=0 */ (__pyx_v_self->selected_obs.data + __pyx_t_22 * __pyx_v_self->selected_obs.strides[0]) ))));

  /* "statsmodels\tsa\statespace\_statespace.pyx":3578
 *                 k += 1
 *         self._obs = &self.selected_obs[0]
 *         self._design = &self.selected_design[0]             # <<<<<<<<<<<<<<
 *         self._obs_cov = &self.selected_obs_cov[0]
 * 
 */
  if (unlikely(!__pyx_v_self->selected_design.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 3578; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
  __pyx_t_23 = 0;
  __pyx_v_self->_design = (&(*((__pyx_t_double_complex *) ( /* dim=0 */ (__pyx_v_self->selected_design.data + __pyx_t_23 * __pyx_v_self->selected_design.strides[0]) ))));

  /* "statsmodels\tsa\statespace\_statespace.pyx":3579
 *         self._obs = &self.selected_obs[0]
 *         self._design = &self.selected_design[0]
 *         self._obs_cov = &self.selected_obs_cov[0]             # <<<<<<<<<<<<<<
 * 
 *     cdef void post_convergence(self):
 */
  if (unlikely(!__pyx_v_self->selected_obs_cov.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 3579; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
  __pyx_t_24 = 0;
  __pyx_v_self->_obs_cov = (&(*((__pyx_t_double_complex *) ( /* dim=0 */ (__pyx_v_self->selected_obs_cov.data + __pyx_t_24 * __pyx_v_self->selected_obs_cov.strides[0]) ))));

  /* "statsmodels\tsa\statespace\_statespace.pyx":3539
 *         # filter
 * 
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  /* "statsmodels\tsa\statespace\_statespace.pyx":3638
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  __pyx_t_1 = __pyx_v_self->t;
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  __pyx_t_2 = __pyx_t_3;
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    /* "statsmodels\tsa\statespace\_statespace.pyx":3643
 *             # `tmp0` array used here, dimension $(m \times m)$
 *             # `tmp1` array used here, dimension $(1 \times 1)$
 *             zcopy(&self.k_states2, self._input_state_cov, &inc, self._tmp0, &inc)             # <<<<<<<<<<<<<<
 *             zaxpy(&self.k_states2, &gamma, self._predicted_state_cov, &inc, self._tmp0, &inc)
 * 
 */
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zcopy((&__pyx_v_self->k_states2), __pyx_v_self->_input_state_cov, (&__pyx_v_inc), __pyx_v_self->_tmp0, (&__pyx_v_inc));

    /* "statsmodels\tsa\statespace\_statespace.pyx":3644
 *             # `tmp1` array used here, dimension $(1 \times 1)$
 *             zcopy(&self.k_states2, self._input_state_cov, &inc, self._tmp0, &inc)
 *             zaxpy(&self.k_states2, &gamma, self._predicted_state_cov, &inc, self._tmp0, &inc)             # <<<<<<<<<<<<<<
 * 
 *             zgemv("N", &inc, &self.k_states2, &alpha, self._tmp0, &inc, self._tmp0, &inc, &beta, self._tmp1, &inc)
 */
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zaxpy((&__pyx_v_self->k_states2), (&__pyx_v_gamma), __pyx_v_self->_predicted_state_cov, (&__pyx_v_inc), __pyx_v_self->_tmp0, (&__pyx_v_inc));

    /* "statsmodels\tsa\statespace\_statespace.pyx":3646
 *             zaxpy(&self.k_states2, &gamma, self._predicted_state_cov, &inc, self._tmp0, &inc)
 * 
 *             zgemv("N", &inc, &self.k_states2, &alpha, self._tmp0, &inc, self._tmp0, &inc, &beta, self._tmp1, &inc)             # <<<<<<<<<<<<<<
 *             if zabs(self._tmp1[0]) < self.tolerance:
 *                 self.converged = 1
 */
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zgemv(__pyx_k_N, (&__pyx_v_inc), (&__pyx_v_self->k_states2), (&__pyx_v_alpha), __pyx_v_self->_tmp0, (&__pyx_v_inc), __pyx_v_self->_tmp0, (&__pyx_v_inc), (&__pyx_v_beta), __pyx_v_self->_tmp1, (&__pyx_v_inc));

    /* "statsmodels\tsa\statespace\_statespace.pyx":3647
 * 
 *             zgemv("N", &inc, &self.k_states2, &alpha, self._tmp0, &inc, self._tmp0, &inc, &beta, self._tmp1, &inc)
 *             if zabs(self._tmp1[0]) < self.tolerance:             # <<<<<<<<<<<<<<
 *                 self.converged = 1
 *                 self.period_converged = self.t
 */
    __pyx_t_2 = ((__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_zabs((__pyx_v_self->_tmp1[0])) < __pyx_v_self->tolerance) != 0);
    if (__pyx_t_2) {

      /* "statsmodels\tsa\statespace\_statespace.pyx":3648
 *             zgemv("N", &inc, &self.k_states2, &alpha, self._tmp0, &inc, self._tmp0, &inc, &beta, self._tmp1, &inc)
 *             if zabs(self._tmp1[0]) < self.tolerance:
 *                 self.converged = 1             # <<<<<<<<<<<<<<
 *                 self.period_converged = self.t
 * 
 */
      __pyx_v_self->converged = 1;

      /* "statsmodels\tsa\statespace\_statespace.pyx":3649
 *             if zabs(self._tmp1[0]) < self.tolerance:
 *                 self.converged = 1
 *                 self.period_converged = self.t             # <<<<<<<<<<<<<<
 * 
 *             # If we just converged, copy the current iteration matrices to the
 */
      __pyx_t_4 = __pyx_v_self->t;
      __pyx_v_self->period_converged = __pyx_t_4;
      goto __pyx_L10;
    }
    __pyx_L10:;

    /* "statsmodels\tsa\statespace\_statespace.pyx":3653
 *             # If we just converged, copy the current iteration matrices to the
 *             # converged storage
 *             if self.converged == 1:             # <<<<<<<<<<<<<<
 *                 # $F_t$
 *                 zcopy(&self.k_endog2, &self.forecast_error_cov[0, 0, forecast_t], &inc, self._converged_forecast_error_cov, &inc)
 */
    __pyx_t_2 = ((__pyx_v_self->converged == 1) != 0);
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      /* "statsmodels\tsa\statespace\_statespace.pyx":3655
 *             if self.converged == 1:
 *                 # $F_t$
 *                 zcopy(&self.k_endog2, &self.forecast_error_cov[0, 0, forecast_t], &inc, self._converged_forecast_error_cov, &inc)             # <<<<<<<<<<<<<<
 *                 # $P_{t|t}$
 *                 zcopy(&self.k_states2, &self.filtered_state_cov[0, 0, filtered_t], &inc, self._converged_filtered_state_cov, &inc)
 */
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      __pyx_t_5 = 0;
      __pyx_t_6 = 0;
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      /* "statsmodels\tsa\statespace\_statespace.pyx":3657
 *                 zcopy(&self.k_endog2, &self.forecast_error_cov[0, 0, forecast_t], &inc, self._converged_forecast_error_cov, &inc)
 *                 # $P_{t|t}$
 *                 zcopy(&self.k_states2, &self.filtered_state_cov[0, 0, filtered_t], &inc, self._converged_filtered_state_cov, &inc)             # <<<<<<<<<<<<<<
 *                 # $P_t$
 *                 zcopy(&self.k_states2, &self.predicted_state_cov[0, 0, predicted_t], &inc, self._converged_predicted_state_cov, &inc)
 */
      if (unlikely(!__pyx_v_self->filtered_state_cov.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 3657; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
      __pyx_t_7 = 0;
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      /* "statsmodels\tsa\statespace\_statespace.pyx":3659
 *                 zcopy(&self.k_states2, &self.filtered_state_cov[0, 0, filtered_t], &inc, self._converged_filtered_state_cov, &inc)
 *                 # $P_t$
 *                 zcopy(&self.k_states2, &self.predicted_state_cov[0, 0, predicted_t], &inc, self._converged_predicted_state_cov, &inc)             # <<<<<<<<<<<<<<
 *                 # $|F_t|$
 *                 self.converged_determinant = self.determinant
 */
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      __pyx_t_10 = 0;
      __pyx_t_11 = 0;
      __pyx_t_12 = __pyx_v_predicted_t;
      __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zcopy((&__pyx_v_self->k_states2), (&(*((__pyx_t_double_complex *) ( /* dim=2 */ (( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_self->predicted_state_cov.data) + __pyx_t_10)) ) + __pyx_t_11 * __pyx_v_self->predicted_state_cov.strides[1]) ) + __pyx_t_12 * __pyx_v_self->predicted_state_cov.strides[2]) )))), (&__pyx_v_inc), __pyx_v_self->_converged_predicted_state_cov, (&__pyx_v_inc));

      /* "statsmodels\tsa\statespace\_statespace.pyx":3661
 *                 zcopy(&self.k_states2, &self.predicted_state_cov[0, 0, predicted_t], &inc, self._converged_predicted_state_cov, &inc)
 *                 # $|F_t|$
 *                 self.converged_determinant = self.determinant             # <<<<<<<<<<<<<<
 * 
 *     cdef void migrate_storage(self):
 */
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      __pyx_v_self->converged_determinant = __pyx_t_13;
      goto __pyx_L11;
    }
    __pyx_L11:;
    goto __pyx_L6;
  }
  __pyx_L6:;

  /* "statsmodels\tsa\statespace\_statespace.pyx":3619
 *                     self.predicted_state_cov[j,i,predicted_t+1] = value
 * 
 *     cdef void check_convergence(self):             # <<<<<<<<<<<<<<
 *         # Constants
 *         cdef:
 */

  /* function exit code */
  goto __pyx_L0;
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/* "statsmodels\tsa\statespace\_statespace.pyx":3663
 *                 self.converged_determinant = self.determinant
 * 
 *     cdef void migrate_storage(self):             # <<<<<<<<<<<<<<
 *         cdef int inc = 1
 * 
 */

static void __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_migrate_storage(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *__pyx_v_self) {
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  Py_ssize_t __pyx_t_44;
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  /* "statsmodels\tsa\statespace\_statespace.pyx":3664
 * 
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 * 
 *         # Forecast: 1 -> 0
 */
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  /* "statsmodels\tsa\statespace\_statespace.pyx":3667
 * 
 *         # Forecast: 1 -> 0
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 */
  __pyx_t_1 = (((__pyx_v_self->conserve_memory & __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_MEMORY_NO_FORECAST) > 0) != 0);
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    /* "statsmodels\tsa\statespace\_statespace.pyx":3668
 *         # Forecast: 1 -> 0
 *         if self.conserve_memory & MEMORY_NO_FORECAST > 0:
 *             zcopy(&self.k_endog, &self.forecast[0, 1], &inc, &self.forecast[0, 0], &inc)             # <<<<<<<<<<<<<<
 *             zcopy(&self.k_endog, &self.forecast_error[0, 1], &inc, &self.forecast_error[0, 0], &inc)
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 */
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    __pyx_t_2 = 0;
    __pyx_t_3 = 1;
    if (unlikely(!__pyx_v_self->forecast.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 3668; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
    __pyx_t_4 = 0;
    __pyx_t_5 = 0;
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zcopy((&__pyx_v_self->k_endog), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_self->forecast.data) + __pyx_t_2)) ) + __pyx_t_3 * __pyx_v_self->forecast.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_self->forecast.data) + __pyx_t_4)) ) + __pyx_t_5 * __pyx_v_self->forecast.strides[1]) )))), (&__pyx_v_inc));

    /* "statsmodels\tsa\statespace\_statespace.pyx":3669
 *         if self.conserve_memory & MEMORY_NO_FORECAST > 0:
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 *             zcopy(&self.k_endog, &self.forecast_error[0, 1], &inc, &self.forecast_error[0, 0], &inc)             # <<<<<<<<<<<<<<
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 */
    if (unlikely(!__pyx_v_self->forecast_error.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 3669; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
    __pyx_t_6 = 0;
    __pyx_t_7 = 1;
    if (unlikely(!__pyx_v_self->forecast_error.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 3669; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
    __pyx_t_8 = 0;
    __pyx_t_9 = 0;
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zcopy((&__pyx_v_self->k_endog), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_self->forecast_error.data) + __pyx_t_6)) ) + __pyx_t_7 * __pyx_v_self->forecast_error.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_self->forecast_error.data) + __pyx_t_8)) ) + __pyx_t_9 * __pyx_v_self->forecast_error.strides[1]) )))), (&__pyx_v_inc));

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 *             zcopy(&self.k_endog, &self.forecast[0, 1], &inc, &self.forecast[0, 0], &inc)
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 *             zcopy(&self.k_endog2, &self.forecast_error_cov[0, 0, 1], &inc, &self.forecast_error_cov[0, 0, 0], &inc)             # <<<<<<<<<<<<<<
 * 
 *         # Filtered: 1 -> 0
 */
    if (unlikely(!__pyx_v_self->forecast_error_cov.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 3670; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
    __pyx_t_10 = 0;
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    __pyx_t_12 = 1;
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    __pyx_t_15 = 0;
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    goto __pyx_L3;
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  __pyx_L3:;

  /* "statsmodels\tsa\statespace\_statespace.pyx":3673
 * 
 *         # Filtered: 1 -> 0
 *         if self.conserve_memory & MEMORY_NO_FILTERED > 0:             # <<<<<<<<<<<<<<
 *             zcopy(&self.k_states, &self.filtered_state[0, 1], &inc, &self.filtered_state[0, 0], &inc)
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 */
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    /* "statsmodels\tsa\statespace\_statespace.pyx":3674
 *         # Filtered: 1 -> 0
 *         if self.conserve_memory & MEMORY_NO_FILTERED > 0:
 *             zcopy(&self.k_states, &self.filtered_state[0, 1], &inc, &self.filtered_state[0, 0], &inc)             # <<<<<<<<<<<<<<
 *             zcopy(&self.k_states2, &self.filtered_state_cov[0, 0, 1], &inc, &self.filtered_state_cov[0, 0, 0], &inc)
 * 
 */
    if (unlikely(!__pyx_v_self->filtered_state.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 3674; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
    __pyx_t_16 = 0;
    __pyx_t_17 = 1;
    if (unlikely(!__pyx_v_self->filtered_state.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 3674; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
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 */
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  /* "statsmodels\tsa\statespace\_statespace.pyx":3773
 *     # error_variance_factor = linalg.cholesky(error_variance, lower=True)
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 */
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  /* "statsmodels\tsa\statespace\_statespace.pyx":3774
 *     zcopy(&k_endog2, &error_variance[0,0], &inc, &forward_factors[0,0], &inc)
 *     zpotrf("L", &k_endog, &forward_factors[0,0], &k_endog, &info)
 *     zcopy(&k_endog2, &forward_factors[0,0], &inc, &backward_factors[0,0], &inc)             # <<<<<<<<<<<<<<
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 */
  __pyx_t_27 = 0;
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  __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zcopy((&__pyx_v_k_endog2), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_forward_factors.data) + __pyx_t_27)) ) + __pyx_t_28 * __pyx_v_forward_factors.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_backward_factors.data) + __pyx_t_29)) ) + __pyx_t_30 * __pyx_v_backward_factors.strides[1]) )))), (&__pyx_v_inc));

  /* "statsmodels\tsa\statespace\_statespace.pyx":3783
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 *     # the last row, correctly ordered, is then used as the coefficients
 *     for s in range(order):  # s = 0, ..., p-1             # <<<<<<<<<<<<<<
 *         if s % 2 == 0:
 *             forwards = &forwards1[0, 0]
 */
  __pyx_t_31 = __pyx_v_order;
  for (__pyx_t_32 = 0; __pyx_t_32 < __pyx_t_31; __pyx_t_32+=1) {
    __pyx_v_s = __pyx_t_32;

    /* "statsmodels\tsa\statespace\_statespace.pyx":3784
 *     # the last row, correctly ordered, is then used as the coefficients
 *     for s in range(order):  # s = 0, ..., p-1
 *         if s % 2 == 0:             # <<<<<<<<<<<<<<
 *             forwards = &forwards1[0, 0]
 *             prev_forwards = &forwards2[0, 0]
 */
    __pyx_t_3 = ((__Pyx_mod_long(__pyx_v_s, 2) == 0) != 0);
    if (__pyx_t_3) {

      /* "statsmodels\tsa\statespace\_statespace.pyx":3785
 *     for s in range(order):  # s = 0, ..., p-1
 *         if s % 2 == 0:
 *             forwards = &forwards1[0, 0]             # <<<<<<<<<<<<<<
 *             prev_forwards = &forwards2[0, 0]
 *             backwards = &backwards1[0, 0]
 */
      __pyx_t_33 = 0;
      __pyx_t_34 = 0;
      __pyx_v_forwards = (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_forwards1.data) + __pyx_t_33)) ) + __pyx_t_34 * __pyx_v_forwards1.strides[1]) ))));

      /* "statsmodels\tsa\statespace\_statespace.pyx":3786
 *         if s % 2 == 0:
 *             forwards = &forwards1[0, 0]
 *             prev_forwards = &forwards2[0, 0]             # <<<<<<<<<<<<<<
 *             backwards = &backwards1[0, 0]
 *             prev_backwards = &backwards2[0, 0]
 */
      __pyx_t_35 = 0;
      __pyx_t_36 = 0;
      __pyx_v_prev_forwards = (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_forwards2.data) + __pyx_t_35)) ) + __pyx_t_36 * __pyx_v_forwards2.strides[1]) ))));

      /* "statsmodels\tsa\statespace\_statespace.pyx":3787
 *             forwards = &forwards1[0, 0]
 *             prev_forwards = &forwards2[0, 0]
 *             backwards = &backwards1[0, 0]             # <<<<<<<<<<<<<<
 *             prev_backwards = &backwards2[0, 0]
 *         else:
 */
      __pyx_t_37 = 0;
      __pyx_t_38 = 0;
      __pyx_v_backwards = (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_backwards1.data) + __pyx_t_37)) ) + __pyx_t_38 * __pyx_v_backwards1.strides[1]) ))));

      /* "statsmodels\tsa\statespace\_statespace.pyx":3788
 *             prev_forwards = &forwards2[0, 0]
 *             backwards = &backwards1[0, 0]
 *             prev_backwards = &backwards2[0, 0]             # <<<<<<<<<<<<<<
 *         else:
 *             forwards = &forwards2[0, 0]
 */
      __pyx_t_39 = 0;
      __pyx_t_40 = 0;
      __pyx_v_prev_backwards = (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_backwards2.data) + __pyx_t_39)) ) + __pyx_t_40 * __pyx_v_backwards2.strides[1]) ))));
      goto __pyx_L6;
    }
    /*else*/ {

      /* "statsmodels\tsa\statespace\_statespace.pyx":3790
 *             prev_backwards = &backwards2[0, 0]
 *         else:
 *             forwards = &forwards2[0, 0]             # <<<<<<<<<<<<<<
 *             prev_forwards = &forwards1[0, 0]
 *             backwards = &backwards2[0, 0]
 */
      __pyx_t_41 = 0;
      __pyx_t_42 = 0;
      __pyx_v_forwards = (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_forwards2.data) + __pyx_t_41)) ) + __pyx_t_42 * __pyx_v_forwards2.strides[1]) ))));

      /* "statsmodels\tsa\statespace\_statespace.pyx":3791
 *         else:
 *             forwards = &forwards2[0, 0]
 *             prev_forwards = &forwards1[0, 0]             # <<<<<<<<<<<<<<
 *             backwards = &backwards2[0, 0]
 *             prev_backwards = &backwards1[0, 0]
 */
      __pyx_t_43 = 0;
      __pyx_t_44 = 0;
      __pyx_v_prev_forwards = (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_forwards1.data) + __pyx_t_43)) ) + __pyx_t_44 * __pyx_v_forwards1.strides[1]) ))));

      /* "statsmodels\tsa\statespace\_statespace.pyx":3792
 *             forwards = &forwards2[0, 0]
 *             prev_forwards = &forwards1[0, 0]
 *             backwards = &backwards2[0, 0]             # <<<<<<<<<<<<<<
 *             prev_backwards = &backwards1[0, 0]
 * 
 */
      __pyx_t_45 = 0;
      __pyx_t_46 = 0;
      __pyx_v_backwards = (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_backwards2.data) + __pyx_t_45)) ) + __pyx_t_46 * __pyx_v_backwards2.strides[1]) ))));

      /* "statsmodels\tsa\statespace\_statespace.pyx":3793
 *             prev_forwards = &forwards1[0, 0]
 *             backwards = &backwards2[0, 0]
 *             prev_backwards = &backwards1[0, 0]             # <<<<<<<<<<<<<<
 * 
 *         # Create the "last" (k = s+1) matrix
 */
      __pyx_t_47 = 0;
      __pyx_t_48 = 0;
      __pyx_v_prev_backwards = (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_backwards1.data) + __pyx_t_47)) ) + __pyx_t_48 * __pyx_v_backwards1.strides[1]) ))));
    }
    __pyx_L6:;

    /* "statsmodels\tsa\statespace\_statespace.pyx":3807
 *         #         lower=True, trans='T').T
 *         # )
 *         for k in range(k_endog):             # <<<<<<<<<<<<<<
 *             zcopy(&k_endog, &partial_autocorrelations[k,s*k_endog], &k_endog, &tmp[0, k], &inc)
 *         ztrtrs("L", "T", "N", &k_endog, &k_endog, &backward_factors[0,0], &k_endog,
 */
    __pyx_t_49 = __pyx_v_k_endog;
    for (__pyx_t_50 = 0; __pyx_t_50 < __pyx_t_49; __pyx_t_50+=1) {
      __pyx_v_k = __pyx_t_50;

      /* "statsmodels\tsa\statespace\_statespace.pyx":3808
 *         # )
 *         for k in range(k_endog):
 *             zcopy(&k_endog, &partial_autocorrelations[k,s*k_endog], &k_endog, &tmp[0, k], &inc)             # <<<<<<<<<<<<<<
 *         ztrtrs("L", "T", "N", &k_endog, &k_endog, &backward_factors[0,0], &k_endog,
 *                                                            &tmp[0, 0], &k_endog, &info)
 */
      __pyx_t_51 = __pyx_v_k;
      __pyx_t_52 = (__pyx_v_s * __pyx_v_k_endog);
      __pyx_t_53 = 0;
      __pyx_t_54 = __pyx_v_k;
      __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zcopy((&__pyx_v_k_endog), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_partial_autocorrelations.data) + __pyx_t_51)) ) + __pyx_t_52 * __pyx_v_partial_autocorrelations.strides[1]) )))), (&__pyx_v_k_endog), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_tmp.data) + __pyx_t_53)) ) + __pyx_t_54 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_inc));
    }

    /* "statsmodels\tsa\statespace\_statespace.pyx":3809
 *         for k in range(k_endog):
 *             zcopy(&k_endog, &partial_autocorrelations[k,s*k_endog], &k_endog, &tmp[0, k], &inc)
 *         ztrtrs("L", "T", "N", &k_endog, &k_endog, &backward_factors[0,0], &k_endog,             # <<<<<<<<<<<<<<
 *                                                            &tmp[0, 0], &k_endog, &info)
 *         # zgemm("N", "T", &k_endog, &k_endog, &k_endog,
 */
    __pyx_t_55 = 0;
    __pyx_t_56 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":3810
 *             zcopy(&k_endog, &partial_autocorrelations[k,s*k_endog], &k_endog, &tmp[0, k], &inc)
 *         ztrtrs("L", "T", "N", &k_endog, &k_endog, &backward_factors[0,0], &k_endog,
 *                                                            &tmp[0, 0], &k_endog, &info)             # <<<<<<<<<<<<<<
 *         # zgemm("N", "T", &k_endog, &k_endog, &k_endog,
 *         #   &alpha, &forward_factors[0,0], &k_endog,
 */
    __pyx_t_57 = 0;
    __pyx_t_58 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":3809
 *         for k in range(k_endog):
 *             zcopy(&k_endog, &partial_autocorrelations[k,s*k_endog], &k_endog, &tmp[0, k], &inc)
 *         ztrtrs("L", "T", "N", &k_endog, &k_endog, &backward_factors[0,0], &k_endog,             # <<<<<<<<<<<<<<
 *                                                            &tmp[0, 0], &k_endog, &info)
 *         # zgemm("N", "T", &k_endog, &k_endog, &k_endog,
 */
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_ztrtrs(__pyx_k_L, __pyx_k_T, __pyx_k_N, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_backward_factors.data) + __pyx_t_55)) ) + __pyx_t_56 * __pyx_v_backward_factors.strides[1]) )))), (&__pyx_v_k_endog), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_tmp.data) + __pyx_t_57)) ) + __pyx_t_58 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_k_endog), (&__pyx_v_info));

    /* "statsmodels\tsa\statespace\_statespace.pyx":3816
 *         #   &beta, &forwards[s*k_endog2], &k_endog)
 *         ztrmm("R", "L", "T", "N", &k_endog, &k_endog,
 *           &alpha, &forward_factors[0,0], &k_endog,             # <<<<<<<<<<<<<<
 *                   &tmp[0, 0], &k_endog)
 *         for k in range(k_endog):
 */
    __pyx_t_59 = 0;
    __pyx_t_60 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":3817
 *         ztrmm("R", "L", "T", "N", &k_endog, &k_endog,
 *           &alpha, &forward_factors[0,0], &k_endog,
 *                   &tmp[0, 0], &k_endog)             # <<<<<<<<<<<<<<
 *         for k in range(k_endog):
 *             zcopy(&k_endog, &tmp[k,0], &k_endog, &forwards[s*k_endog2 + k*k_endog], &inc)
 */
    __pyx_t_61 = 0;
    __pyx_t_62 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":3815
 *         #           &tmp[0, 0], &k_endog,
 *         #   &beta, &forwards[s*k_endog2], &k_endog)
 *         ztrmm("R", "L", "T", "N", &k_endog, &k_endog,             # <<<<<<<<<<<<<<
 *           &alpha, &forward_factors[0,0], &k_endog,
 *                   &tmp[0, 0], &k_endog)
 */
    __pyx_v_ztrmm(__pyx_k_R, __pyx_k_L, __pyx_k_T, __pyx_k_N, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_alpha), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_forward_factors.data) + __pyx_t_59)) ) + __pyx_t_60 * __pyx_v_forward_factors.strides[1]) )))), (&__pyx_v_k_endog), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_tmp.data) + __pyx_t_61)) ) + __pyx_t_62 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_k_endog));

    /* "statsmodels\tsa\statespace\_statespace.pyx":3818
 *           &alpha, &forward_factors[0,0], &k_endog,
 *                   &tmp[0, 0], &k_endog)
 *         for k in range(k_endog):             # <<<<<<<<<<<<<<
 *             zcopy(&k_endog, &tmp[k,0], &k_endog, &forwards[s*k_endog2 + k*k_endog], &inc)
 * 
 */
    __pyx_t_49 = __pyx_v_k_endog;
    for (__pyx_t_50 = 0; __pyx_t_50 < __pyx_t_49; __pyx_t_50+=1) {
      __pyx_v_k = __pyx_t_50;

      /* "statsmodels\tsa\statespace\_statespace.pyx":3819
 *                   &tmp[0, 0], &k_endog)
 *         for k in range(k_endog):
 *             zcopy(&k_endog, &tmp[k,0], &k_endog, &forwards[s*k_endog2 + k*k_endog], &inc)             # <<<<<<<<<<<<<<
 * 
 *         # P' L^{-1} = x
 */
      __pyx_t_63 = __pyx_v_k;
      __pyx_t_64 = 0;
      __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zcopy((&__pyx_v_k_endog), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_tmp.data) + __pyx_t_63)) ) + __pyx_t_64 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_k_endog), (&(__pyx_v_forwards[((__pyx_v_s * __pyx_v_k_endog2) + (__pyx_v_k * __pyx_v_k_endog))])), (&__pyx_v_inc));
    }

    /* "statsmodels\tsa\statespace\_statespace.pyx":3830
 *         #         lower=True, trans='T').T
 *         # )
 *         zcopy(&k_endog2, &partial_autocorrelations[0, s*k_endog], &inc, &tmp[0, 0], &inc)             # <<<<<<<<<<<<<<
 *         ztrtrs("L", "T", "N", &k_endog, &k_endog, &forward_factors[0, 0], &k_endog,
 *                                                            &tmp[0, 0], &k_endog, &info)
 */
    __pyx_t_65 = 0;
    __pyx_t_49 = (__pyx_v_s * __pyx_v_k_endog);
    __pyx_t_66 = 0;
    __pyx_t_67 = 0;
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zcopy((&__pyx_v_k_endog2), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_partial_autocorrelations.data) + __pyx_t_65)) ) + __pyx_t_49 * __pyx_v_partial_autocorrelations.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_tmp.data) + __pyx_t_66)) ) + __pyx_t_67 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_inc));

    /* "statsmodels\tsa\statespace\_statespace.pyx":3831
 *         # )
 *         zcopy(&k_endog2, &partial_autocorrelations[0, s*k_endog], &inc, &tmp[0, 0], &inc)
 *         ztrtrs("L", "T", "N", &k_endog, &k_endog, &forward_factors[0, 0], &k_endog,             # <<<<<<<<<<<<<<
 *                                                            &tmp[0, 0], &k_endog, &info)
 *         # zgemm("N", "T", &k_endog, &k_endog, &k_endog,
 */
    __pyx_t_68 = 0;
    __pyx_t_69 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":3832
 *         zcopy(&k_endog2, &partial_autocorrelations[0, s*k_endog], &inc, &tmp[0, 0], &inc)
 *         ztrtrs("L", "T", "N", &k_endog, &k_endog, &forward_factors[0, 0], &k_endog,
 *                                                            &tmp[0, 0], &k_endog, &info)             # <<<<<<<<<<<<<<
 *         # zgemm("N", "T", &k_endog, &k_endog, &k_endog,
 *         #   &alpha, &backward_factors[0, 0], &k_endog,
 */
    __pyx_t_70 = 0;
    __pyx_t_71 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":3831
 *         # )
 *         zcopy(&k_endog2, &partial_autocorrelations[0, s*k_endog], &inc, &tmp[0, 0], &inc)
 *         ztrtrs("L", "T", "N", &k_endog, &k_endog, &forward_factors[0, 0], &k_endog,             # <<<<<<<<<<<<<<
 *                                                            &tmp[0, 0], &k_endog, &info)
 *         # zgemm("N", "T", &k_endog, &k_endog, &k_endog,
 */
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_ztrtrs(__pyx_k_L, __pyx_k_T, __pyx_k_N, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_forward_factors.data) + __pyx_t_68)) ) + __pyx_t_69 * __pyx_v_forward_factors.strides[1]) )))), (&__pyx_v_k_endog), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_tmp.data) + __pyx_t_70)) ) + __pyx_t_71 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_k_endog), (&__pyx_v_info));

    /* "statsmodels\tsa\statespace\_statespace.pyx":3838
 *         #   &beta, &backwards[s * k_endog2], &k_endog)
 *         ztrmm("R", "L", "T", "N", &k_endog, &k_endog,
 *           &alpha, &backward_factors[0,0], &k_endog,             # <<<<<<<<<<<<<<
 *                   &tmp[0, 0], &k_endog)
 *         for k in range(k_endog):
 */
    __pyx_t_72 = 0;
    __pyx_t_73 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":3839
 *         ztrmm("R", "L", "T", "N", &k_endog, &k_endog,
 *           &alpha, &backward_factors[0,0], &k_endog,
 *                   &tmp[0, 0], &k_endog)             # <<<<<<<<<<<<<<
 *         for k in range(k_endog):
 *             zcopy(&k_endog, &tmp[k,0], &k_endog, &backwards[s*k_endog2 + k*k_endog], &inc)
 */
    __pyx_t_74 = 0;
    __pyx_t_75 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":3837
 *         #           &tmp[0, 0], &k_endog,
 *         #   &beta, &backwards[s * k_endog2], &k_endog)
 *         ztrmm("R", "L", "T", "N", &k_endog, &k_endog,             # <<<<<<<<<<<<<<
 *           &alpha, &backward_factors[0,0], &k_endog,
 *                   &tmp[0, 0], &k_endog)
 */
    __pyx_v_ztrmm(__pyx_k_R, __pyx_k_L, __pyx_k_T, __pyx_k_N, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_alpha), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_backward_factors.data) + __pyx_t_72)) ) + __pyx_t_73 * __pyx_v_backward_factors.strides[1]) )))), (&__pyx_v_k_endog), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_tmp.data) + __pyx_t_74)) ) + __pyx_t_75 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_k_endog));

    /* "statsmodels\tsa\statespace\_statespace.pyx":3840
 *           &alpha, &backward_factors[0,0], &k_endog,
 *                   &tmp[0, 0], &k_endog)
 *         for k in range(k_endog):             # <<<<<<<<<<<<<<
 *             zcopy(&k_endog, &tmp[k,0], &k_endog, &backwards[s*k_endog2 + k*k_endog], &inc)
 * 
 */
    __pyx_t_50 = __pyx_v_k_endog;
    for (__pyx_t_76 = 0; __pyx_t_76 < __pyx_t_50; __pyx_t_76+=1) {
      __pyx_v_k = __pyx_t_76;

      /* "statsmodels\tsa\statespace\_statespace.pyx":3841
 *                   &tmp[0, 0], &k_endog)
 *         for k in range(k_endog):
 *             zcopy(&k_endog, &tmp[k,0], &k_endog, &backwards[s*k_endog2 + k*k_endog], &inc)             # <<<<<<<<<<<<<<
 * 
 *         # Update the variance
 */
      __pyx_t_77 = __pyx_v_k;
      __pyx_t_78 = 0;
      __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zcopy((&__pyx_v_k_endog), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_tmp.data) + __pyx_t_77)) ) + __pyx_t_78 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_k_endog), (&(__pyx_v_backwards[((__pyx_v_s * __pyx_v_k_endog2) + (__pyx_v_k * __pyx_v_k_endog))])), (&__pyx_v_inc));
    }

    /* "statsmodels\tsa\statespace\_statespace.pyx":3850
 *         # tmpT = np.dot(backward_variance.T, forwards[:, s*k_endog:(s+1)*k_endog].T)
 *         zgemm("T", "T", &k_endog, &k_endog, &k_endog,
 *           &alpha, &backward_variance[0, 0], &k_endog,             # <<<<<<<<<<<<<<
 *                   &forwards[s * k_endog2], &k_endog,
 *           &beta, &tmp[0, 0], &k_endog)
 */
    __pyx_t_79 = 0;
    __pyx_t_80 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":3852
 *           &alpha, &backward_variance[0, 0], &k_endog,
 *                   &forwards[s * k_endog2], &k_endog,
 *           &beta, &tmp[0, 0], &k_endog)             # <<<<<<<<<<<<<<
 *         # autocovariances[:, (s+1)*k_endog:(s+2)*k_endog] = tmp.copy().T
 *         zcopy(&k_endog2, &tmp[0, 0], &inc, &autocovariances[0, (s+1)*k_endog], &inc)
 */
    __pyx_t_81 = 0;
    __pyx_t_82 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":3849
 *         # tmp = np.dot(forwards[:, s*k_endog:(s+1)*k_endog], backward_variance)
 *         # tmpT = np.dot(backward_variance.T, forwards[:, s*k_endog:(s+1)*k_endog].T)
 *         zgemm("T", "T", &k_endog, &k_endog, &k_endog,             # <<<<<<<<<<<<<<
 *           &alpha, &backward_variance[0, 0], &k_endog,
 *                   &forwards[s * k_endog2], &k_endog,
 */
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zgemm(__pyx_k_T, __pyx_k_T, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_alpha), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_backward_variance.data) + __pyx_t_79)) ) + __pyx_t_80 * __pyx_v_backward_variance.strides[1]) )))), (&__pyx_v_k_endog), (&(__pyx_v_forwards[(__pyx_v_s * __pyx_v_k_endog2)])), (&__pyx_v_k_endog), (&__pyx_v_beta), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_tmp.data) + __pyx_t_81)) ) + __pyx_t_82 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_k_endog));

    /* "statsmodels\tsa\statespace\_statespace.pyx":3854
 *           &beta, &tmp[0, 0], &k_endog)
 *         # autocovariances[:, (s+1)*k_endog:(s+2)*k_endog] = tmp.copy().T
 *         zcopy(&k_endog2, &tmp[0, 0], &inc, &autocovariances[0, (s+1)*k_endog], &inc)             # <<<<<<<<<<<<<<
 * 
 *         # Create the remaining k = 1, ..., s matrices,
 */
    __pyx_t_83 = 0;
    __pyx_t_84 = 0;
    __pyx_t_85 = 0;
    __pyx_t_86 = ((__pyx_v_s + 1) * __pyx_v_k_endog);
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zcopy((&__pyx_v_k_endog2), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_tmp.data) + __pyx_t_83)) ) + __pyx_t_84 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_autocovariances.data) + __pyx_t_85)) ) + __pyx_t_86 * __pyx_v_autocovariances.strides[1]) )))), (&__pyx_v_inc));

    /* "statsmodels\tsa\statespace\_statespace.pyx":3858
 *         # Create the remaining k = 1, ..., s matrices,
 *         # only has an effect if s >= 1
 *         for k in range(s):             # <<<<<<<<<<<<<<
 *             # forwards[:, k*k_endog:(k+1)*k_endog] = (
 *             #     prev_forwards[:, k*k_endog:(k+1)*k_endog] -
 */
    __pyx_t_50 = __pyx_v_s;
    for (__pyx_t_76 = 0; __pyx_t_76 < __pyx_t_50; __pyx_t_76+=1) {
      __pyx_v_k = __pyx_t_76;

      /* "statsmodels\tsa\statespace\_statespace.pyx":3866
 *             #     )
 *             # )
 *             zcopy(&k_endog2, &prev_forwards[k * k_endog2], &inc, &forwards[k * k_endog2], &inc)             # <<<<<<<<<<<<<<
 *             zgemm("N", "N", &k_endog, &k_endog, &k_endog,
 *               &gamma, &forwards[s * k_endog2], &k_endog,
 */
      __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zcopy((&__pyx_v_k_endog2), (&(__pyx_v_prev_forwards[(__pyx_v_k * __pyx_v_k_endog2)])), (&__pyx_v_inc), (&(__pyx_v_forwards[(__pyx_v_k * __pyx_v_k_endog2)])), (&__pyx_v_inc));

      /* "statsmodels\tsa\statespace\_statespace.pyx":3867
 *             # )
 *             zcopy(&k_endog2, &prev_forwards[k * k_endog2], &inc, &forwards[k * k_endog2], &inc)
 *             zgemm("N", "N", &k_endog, &k_endog, &k_endog,             # <<<<<<<<<<<<<<
 *               &gamma, &forwards[s * k_endog2], &k_endog,
 *                       &prev_backwards[(s - k - 1) * k_endog2], &k_endog,
 */
      __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zgemm(__pyx_k_N, __pyx_k_N, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_gamma), (&(__pyx_v_forwards[(__pyx_v_s * __pyx_v_k_endog2)])), (&__pyx_v_k_endog), (&(__pyx_v_prev_backwards[(((__pyx_v_s - __pyx_v_k) - 1) * __pyx_v_k_endog2)])), (&__pyx_v_k_endog), (&__pyx_v_alpha), (&(__pyx_v_forwards[(__pyx_v_k * __pyx_v_k_endog2)])), (&__pyx_v_k_endog));

      /* "statsmodels\tsa\statespace\_statespace.pyx":3879
 *             #     )
 *             # )
 *             zcopy(&k_endog2, &prev_backwards[k * k_endog2], &inc, &backwards[k * k_endog2], &inc)             # <<<<<<<<<<<<<<
 *             zgemm("N", "N", &k_endog, &k_endog, &k_endog,
 *               &gamma, &backwards[s * k_endog2], &k_endog,
 */
      __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zcopy((&__pyx_v_k_endog2), (&(__pyx_v_prev_backwards[(__pyx_v_k * __pyx_v_k_endog2)])), (&__pyx_v_inc), (&(__pyx_v_backwards[(__pyx_v_k * __pyx_v_k_endog2)])), (&__pyx_v_inc));

      /* "statsmodels\tsa\statespace\_statespace.pyx":3880
 *             # )
 *             zcopy(&k_endog2, &prev_backwards[k * k_endog2], &inc, &backwards[k * k_endog2], &inc)
 *             zgemm("N", "N", &k_endog, &k_endog, &k_endog,             # <<<<<<<<<<<<<<
 *               &gamma, &backwards[s * k_endog2], &k_endog,
 *                       &prev_forwards[(s - k - 1) * k_endog2], &k_endog,
 */
      __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zgemm(__pyx_k_N, __pyx_k_N, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_gamma), (&(__pyx_v_backwards[(__pyx_v_s * __pyx_v_k_endog2)])), (&__pyx_v_k_endog), (&(__pyx_v_prev_forwards[(((__pyx_v_s - __pyx_v_k) - 1) * __pyx_v_k_endog2)])), (&__pyx_v_k_endog), (&__pyx_v_alpha), (&(__pyx_v_backwards[(__pyx_v_k * __pyx_v_k_endog2)])), (&__pyx_v_k_endog));

      /* "statsmodels\tsa\statespace\_statespace.pyx":3890
 *             # )
 *             zgemm("N", "T", &k_endog, &k_endog, &k_endog,
 *               &alpha, &autocovariances[0, (k+1)*k_endog], &k_endog,             # <<<<<<<<<<<<<<
 *                       &prev_forwards[(s - k - 1) * k_endog2], &k_endog,
 *               &alpha, &autocovariances[0, (s+1)*k_endog], &k_endog)
 */
      __pyx_t_87 = 0;
      __pyx_t_88 = ((__pyx_v_k + 1) * __pyx_v_k_endog);

      /* "statsmodels\tsa\statespace\_statespace.pyx":3892
 *               &alpha, &autocovariances[0, (k+1)*k_endog], &k_endog,
 *                       &prev_forwards[(s - k - 1) * k_endog2], &k_endog,
 *               &alpha, &autocovariances[0, (s+1)*k_endog], &k_endog)             # <<<<<<<<<<<<<<
 * 
 *         # Create forward and backwards variances
 */
      __pyx_t_89 = 0;
      __pyx_t_90 = ((__pyx_v_s + 1) * __pyx_v_k_endog);

      /* "statsmodels\tsa\statespace\_statespace.pyx":3889
 *             #     prev_forwards[:, (s-k-1)*k_endog:(s-k)*k_endog].T
 *             # )
 *             zgemm("N", "T", &k_endog, &k_endog, &k_endog,             # <<<<<<<<<<<<<<
 *               &alpha, &autocovariances[0, (k+1)*k_endog], &k_endog,
 *                       &prev_forwards[(s - k - 1) * k_endog2], &k_endog,
 */
      __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zgemm(__pyx_k_N, __pyx_k_T, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_alpha), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_autocovariances.data) + __pyx_t_87)) ) + __pyx_t_88 * __pyx_v_autocovariances.strides[1]) )))), (&__pyx_v_k_endog), (&(__pyx_v_prev_forwards[(((__pyx_v_s - __pyx_v_k) - 1) * __pyx_v_k_endog2)])), (&__pyx_v_k_endog), (&__pyx_v_alpha), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_autocovariances.data) + __pyx_t_89)) ) + __pyx_t_90 * __pyx_v_autocovariances.strides[1]) )))), (&__pyx_v_k_endog));
    }

    /* "statsmodels\tsa\statespace\_statespace.pyx":3904
 *         zgemm("N", "N", &k_endog, &k_endog, &k_endog,
 *           &alpha, &backwards[s * k_endog2], &k_endog,
 *                   &forward_variance[0, 0], &k_endog,             # <<<<<<<<<<<<<<
 *           &beta, &tmp2[0, 0], &k_endog)
 *         zgemm("N", "T", &k_endog, &k_endog, &k_endog,
 */
    __pyx_t_91 = 0;
    __pyx_t_92 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":3905
 *           &alpha, &backwards[s * k_endog2], &k_endog,
 *                   &forward_variance[0, 0], &k_endog,
 *           &beta, &tmp2[0, 0], &k_endog)             # <<<<<<<<<<<<<<
 *         zgemm("N", "T", &k_endog, &k_endog, &k_endog,
 *           &gamma, &tmp2[0, 0], &k_endog,
 */
    __pyx_t_93 = 0;
    __pyx_t_94 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":3902
 *         #     )
 *         # )
 *         zgemm("N", "N", &k_endog, &k_endog, &k_endog,             # <<<<<<<<<<<<<<
 *           &alpha, &backwards[s * k_endog2], &k_endog,
 *                   &forward_variance[0, 0], &k_endog,
 */
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zgemm(__pyx_k_N, __pyx_k_N, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_alpha), (&(__pyx_v_backwards[(__pyx_v_s * __pyx_v_k_endog2)])), (&__pyx_v_k_endog), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_forward_variance.data) + __pyx_t_91)) ) + __pyx_t_92 * __pyx_v_forward_variance.strides[1]) )))), (&__pyx_v_k_endog), (&__pyx_v_beta), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_tmp2.data) + __pyx_t_93)) ) + __pyx_t_94 * __pyx_v_tmp2.strides[1]) )))), (&__pyx_v_k_endog));

    /* "statsmodels\tsa\statespace\_statespace.pyx":3907
 *           &beta, &tmp2[0, 0], &k_endog)
 *         zgemm("N", "T", &k_endog, &k_endog, &k_endog,
 *           &gamma, &tmp2[0, 0], &k_endog,             # <<<<<<<<<<<<<<
 *                   &backwards[s * k_endog2], &k_endog,
 *           &alpha, &backward_variance[0, 0], &k_endog)
 */
    __pyx_t_95 = 0;
    __pyx_t_96 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":3909
 *           &gamma, &tmp2[0, 0], &k_endog,
 *                   &backwards[s * k_endog2], &k_endog,
 *           &alpha, &backward_variance[0, 0], &k_endog)             # <<<<<<<<<<<<<<
 *         # forward_variance = (
 *         #     forward_variance -
 */
    __pyx_t_97 = 0;
    __pyx_t_98 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":3906
 *                   &forward_variance[0, 0], &k_endog,
 *           &beta, &tmp2[0, 0], &k_endog)
 *         zgemm("N", "T", &k_endog, &k_endog, &k_endog,             # <<<<<<<<<<<<<<
 *           &gamma, &tmp2[0, 0], &k_endog,
 *                   &backwards[s * k_endog2], &k_endog,
 */
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zgemm(__pyx_k_N, __pyx_k_T, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_gamma), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_tmp2.data) + __pyx_t_95)) ) + __pyx_t_96 * __pyx_v_tmp2.strides[1]) )))), (&__pyx_v_k_endog), (&(__pyx_v_backwards[(__pyx_v_s * __pyx_v_k_endog2)])), (&__pyx_v_k_endog), (&__pyx_v_alpha), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_backward_variance.data) + __pyx_t_97)) ) + __pyx_t_98 * __pyx_v_backward_variance.strides[1]) )))), (&__pyx_v_k_endog));

    /* "statsmodels\tsa\statespace\_statespace.pyx":3919
 *         # )
 *         zgemm("T", "T", &k_endog, &k_endog, &k_endog,
 *           &gamma, &tmp[0, 0], &k_endog,             # <<<<<<<<<<<<<<
 *                   &forwards[s * k_endog2], &k_endog,
 *           &alpha, &forward_variance[0, 0], &k_endog)
 */
    __pyx_t_99 = 0;
    __pyx_t_100 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":3921
 *           &gamma, &tmp[0, 0], &k_endog,
 *                   &forwards[s * k_endog2], &k_endog,
 *           &alpha, &forward_variance[0, 0], &k_endog)             # <<<<<<<<<<<<<<
 * 
 *         # Cholesky factors
 */
    __pyx_t_101 = 0;
    __pyx_t_102 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":3918
 *         #     np.dot(tmpT.T, forwards[:, s*k_endog:(s+1)*k_endog].T)
 *         # )
 *         zgemm("T", "T", &k_endog, &k_endog, &k_endog,             # <<<<<<<<<<<<<<
 *           &gamma, &tmp[0, 0], &k_endog,
 *                   &forwards[s * k_endog2], &k_endog,
 */
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zgemm(__pyx_k_T, __pyx_k_T, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_gamma), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_tmp.data) + __pyx_t_99)) ) + __pyx_t_100 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_k_endog), (&(__pyx_v_forwards[(__pyx_v_s * __pyx_v_k_endog2)])), (&__pyx_v_k_endog), (&__pyx_v_alpha), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_forward_variance.data) + __pyx_t_101)) ) + __pyx_t_102 * __pyx_v_forward_variance.strides[1]) )))), (&__pyx_v_k_endog));

    /* "statsmodels\tsa\statespace\_statespace.pyx":3926
 *         # forward_factors = linalg.cholesky(forward_variance, lower=True)
 *         # backward_factors =  linalg.cholesky(backward_variance, lower=True)
 *         zcopy(&k_endog2, &forward_variance[0,0], &inc, &forward_factors[0,0], &inc)             # <<<<<<<<<<<<<<
 *         zpotrf("L", &k_endog, &forward_factors[0,0], &k_endog, &info)
 *         zcopy(&k_endog2, &backward_variance[0,0], &inc, &backward_factors[0,0], &inc)
 */
    __pyx_t_103 = 0;
    __pyx_t_104 = 0;
    __pyx_t_105 = 0;
    __pyx_t_106 = 0;
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zcopy((&__pyx_v_k_endog2), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_forward_variance.data) + __pyx_t_103)) ) + __pyx_t_104 * __pyx_v_forward_variance.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_forward_factors.data) + __pyx_t_105)) ) + __pyx_t_106 * __pyx_v_forward_factors.strides[1]) )))), (&__pyx_v_inc));

    /* "statsmodels\tsa\statespace\_statespace.pyx":3927
 *         # backward_factors =  linalg.cholesky(backward_variance, lower=True)
 *         zcopy(&k_endog2, &forward_variance[0,0], &inc, &forward_factors[0,0], &inc)
 *         zpotrf("L", &k_endog, &forward_factors[0,0], &k_endog, &info)             # <<<<<<<<<<<<<<
 *         zcopy(&k_endog2, &backward_variance[0,0], &inc, &backward_factors[0,0], &inc)
 *         zpotrf("L", &k_endog, &backward_factors[0,0], &k_endog, &info)
 */
    __pyx_t_107 = 0;
    __pyx_t_108 = 0;
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zpotrf(__pyx_k_L, (&__pyx_v_k_endog), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_forward_factors.data) + __pyx_t_107)) ) + __pyx_t_108 * __pyx_v_forward_factors.strides[1]) )))), (&__pyx_v_k_endog), (&__pyx_v_info));

    /* "statsmodels\tsa\statespace\_statespace.pyx":3928
 *         zcopy(&k_endog2, &forward_variance[0,0], &inc, &forward_factors[0,0], &inc)
 *         zpotrf("L", &k_endog, &forward_factors[0,0], &k_endog, &info)
 *         zcopy(&k_endog2, &backward_variance[0,0], &inc, &backward_factors[0,0], &inc)             # <<<<<<<<<<<<<<
 *         zpotrf("L", &k_endog, &backward_factors[0,0], &k_endog, &info)
 * 
 */
    __pyx_t_109 = 0;
    __pyx_t_110 = 0;
    __pyx_t_111 = 0;
    __pyx_t_112 = 0;
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zcopy((&__pyx_v_k_endog2), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_backward_variance.data) + __pyx_t_109)) ) + __pyx_t_110 * __pyx_v_backward_variance.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_backward_factors.data) + __pyx_t_111)) ) + __pyx_t_112 * __pyx_v_backward_factors.strides[1]) )))), (&__pyx_v_inc));

    /* "statsmodels\tsa\statespace\_statespace.pyx":3929
 *         zpotrf("L", &k_endog, &forward_factors[0,0], &k_endog, &info)
 *         zcopy(&k_endog2, &backward_variance[0,0], &inc, &backward_factors[0,0], &inc)
 *         zpotrf("L", &k_endog, &backward_factors[0,0], &k_endog, &info)             # <<<<<<<<<<<<<<
 * 
 * 
 */
    __pyx_t_113 = 0;
    __pyx_t_114 = 0;
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zpotrf(__pyx_k_L, (&__pyx_v_k_endog), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_backward_factors.data) + __pyx_t_113)) ) + __pyx_t_114 * __pyx_v_backward_factors.strides[1]) )))), (&__pyx_v_k_endog), (&__pyx_v_info));
  }

  /* "statsmodels\tsa\statespace\_statespace.pyx":3934
 *     # If we do not want to use the transformed variance, we need to
 *     # adjust the constrained matrices, as presented in Lemma 2.3, see above
 *     if not transform_variance:             # <<<<<<<<<<<<<<
 *         if order % 2 == 0:
 *             forwards = &forwards2[0,0]
 */
  __pyx_t_3 = ((!(__pyx_v_transform_variance != 0)) != 0);
  if (__pyx_t_3) {

    /* "statsmodels\tsa\statespace\_statespace.pyx":3935
 *     # adjust the constrained matrices, as presented in Lemma 2.3, see above
 *     if not transform_variance:
 *         if order % 2 == 0:             # <<<<<<<<<<<<<<
 *             forwards = &forwards2[0,0]
 *         else:
 */
    __pyx_t_3 = ((__Pyx_mod_long(__pyx_v_order, 2) == 0) != 0);
    if (__pyx_t_3) {

      /* "statsmodels\tsa\statespace\_statespace.pyx":3936
 *     if not transform_variance:
 *         if order % 2 == 0:
 *             forwards = &forwards2[0,0]             # <<<<<<<<<<<<<<
 *         else:
 *             forwards = &forwards1[0,0]
 */
      __pyx_t_115 = 0;
      __pyx_t_116 = 0;
      __pyx_v_forwards = (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_forwards2.data) + __pyx_t_115)) ) + __pyx_t_116 * __pyx_v_forwards2.strides[1]) ))));
      goto __pyx_L16;
    }
    /*else*/ {

      /* "statsmodels\tsa\statespace\_statespace.pyx":3938
 *             forwards = &forwards2[0,0]
 *         else:
 *             forwards = &forwards1[0,0]             # <<<<<<<<<<<<<<
 * 
 *         # Here, we need to construct T such that:
 */
      __pyx_t_117 = 0;
      __pyx_t_118 = 0;
      __pyx_v_forwards = (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_forwards1.data) + __pyx_t_117)) ) + __pyx_t_118 * __pyx_v_forwards1.strides[1]) ))));
    }
    __pyx_L16:;

    /* "statsmodels\tsa\statespace\_statespace.pyx":3949
 *         # initial_variance_factor = np.linalg.cholesky(initial_variance)
 *         # L'
 *         zpotrf("U", &k_endog, &initial_variance[0,0], &k_endog, &info)             # <<<<<<<<<<<<<<
 *         # transformed_variance_factor = np.linalg.cholesky(variance)
 *         # M'
 */
    if (unlikely(!__pyx_v_initial_variance.memview)) { __Pyx_RaiseUnboundLocalError("initial_variance"); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 3949; __pyx_clineno = __LINE__; goto __pyx_L1_error;} }
    __pyx_t_119 = 0;
    __pyx_t_120 = 0;
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zpotrf(__pyx_k_U, (&__pyx_v_k_endog), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_initial_variance.data) + __pyx_t_119)) ) + __pyx_t_120 * __pyx_v_initial_variance.strides[1]) )))), (&__pyx_v_k_endog), (&__pyx_v_info));

    /* "statsmodels\tsa\statespace\_statespace.pyx":3952
 *         # transformed_variance_factor = np.linalg.cholesky(variance)
 *         # M'
 *         zcopy(&k_endog2, &forward_variance[0,0], &inc, &tmp[0,0], &inc)             # <<<<<<<<<<<<<<
 *         zpotrf("U", &k_endog, &tmp[0,0], &k_endog, &info)
 *         # zpotri("L", &k_endog, &tmp[0,0], &k_endog, &info)
 */
    __pyx_t_121 = 0;
    __pyx_t_122 = 0;
    __pyx_t_123 = 0;
    __pyx_t_124 = 0;
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zcopy((&__pyx_v_k_endog2), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_forward_variance.data) + __pyx_t_121)) ) + __pyx_t_122 * __pyx_v_forward_variance.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_tmp.data) + __pyx_t_123)) ) + __pyx_t_124 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_inc));

    /* "statsmodels\tsa\statespace\_statespace.pyx":3953
 *         # M'
 *         zcopy(&k_endog2, &forward_variance[0,0], &inc, &tmp[0,0], &inc)
 *         zpotrf("U", &k_endog, &tmp[0,0], &k_endog, &info)             # <<<<<<<<<<<<<<
 *         # zpotri("L", &k_endog, &tmp[0,0], &k_endog, &info)
 * 
 */
    __pyx_t_125 = 0;
    __pyx_t_126 = 0;
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zpotrf(__pyx_k_U, (&__pyx_v_k_endog), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_tmp.data) + __pyx_t_125)) ) + __pyx_t_126 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_k_endog), (&__pyx_v_info));

    /* "statsmodels\tsa\statespace\_statespace.pyx":3958
 *         # We need to zero out the lower triangle of L', because ?trtrs only
 *         # knows that M' is upper triangular
 *         for s in range(k_endog - 1):          # column             # <<<<<<<<<<<<<<
 *             for k in range(s+1, k_endog):     # row
 *                 initial_variance[k, s] = 0
 */
    __pyx_t_127 = (__pyx_v_k_endog - 1);
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      __pyx_v_s = __pyx_t_31;

      /* "statsmodels\tsa\statespace\_statespace.pyx":3959
 *         # knows that M' is upper triangular
 *         for s in range(k_endog - 1):          # column
 *             for k in range(s+1, k_endog):     # row             # <<<<<<<<<<<<<<
 *                 initial_variance[k, s] = 0
 * 
 */
      __pyx_t_32 = __pyx_v_k_endog;
      for (__pyx_t_50 = (__pyx_v_s + 1); __pyx_t_50 < __pyx_t_32; __pyx_t_50+=1) {
        __pyx_v_k = __pyx_t_50;

        /* "statsmodels\tsa\statespace\_statespace.pyx":3960
 *         for s in range(k_endog - 1):          # column
 *             for k in range(s+1, k_endog):     # row
 *                 initial_variance[k, s] = 0             # <<<<<<<<<<<<<<
 * 
 *         # Note that T is lower triangular
 */
        if (unlikely(!__pyx_v_initial_variance.memview)) { __Pyx_RaiseUnboundLocalError("initial_variance"); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 3960; __pyx_clineno = __LINE__; goto __pyx_L1_error;} }
        __pyx_t_76 = __pyx_v_k;
        __pyx_t_128 = __pyx_v_s;
        *((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_initial_variance.data) + __pyx_t_76)) ) + __pyx_t_128 * __pyx_v_initial_variance.strides[1]) )) = __pyx_t_double_complex_from_parts(0, 0);
      }
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    /* "statsmodels\tsa\statespace\_statespace.pyx":3967
 *         # transform = np.dot(initial_variance_factor,
 *         #                    np.linalg.inv(transformed_variance_factor))
 *         ztrtrs("U", "N", "N", &k_endog, &k_endog, &tmp[0,0], &k_endog,             # <<<<<<<<<<<<<<
 *                                                            &initial_variance[0, 0], &k_endog, &info)
 *         # Now:
 */
    __pyx_t_129 = 0;
    __pyx_t_130 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":3968
 *         #                    np.linalg.inv(transformed_variance_factor))
 *         ztrtrs("U", "N", "N", &k_endog, &k_endog, &tmp[0,0], &k_endog,
 *                                                            &initial_variance[0, 0], &k_endog, &info)             # <<<<<<<<<<<<<<
 *         # Now:
 *         # initial_variance = T'
 */
    if (unlikely(!__pyx_v_initial_variance.memview)) { __Pyx_RaiseUnboundLocalError("initial_variance"); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 3968; __pyx_clineno = __LINE__; goto __pyx_L1_error;} }
    __pyx_t_131 = 0;
    __pyx_t_132 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":3967
 *         # transform = np.dot(initial_variance_factor,
 *         #                    np.linalg.inv(transformed_variance_factor))
 *         ztrtrs("U", "N", "N", &k_endog, &k_endog, &tmp[0,0], &k_endog,             # <<<<<<<<<<<<<<
 *                                                            &initial_variance[0, 0], &k_endog, &info)
 *         # Now:
 */
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_ztrtrs(__pyx_k_U, __pyx_k_N, __pyx_k_N, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_tmp.data) + __pyx_t_129)) ) + __pyx_t_130 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_k_endog), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_initial_variance.data) + __pyx_t_131)) ) + __pyx_t_132 * __pyx_v_initial_variance.strides[1]) )))), (&__pyx_v_k_endog), (&__pyx_v_info));

    /* "statsmodels\tsa\statespace\_statespace.pyx":3972
 *         # initial_variance = T'
 * 
 *         for s in range(order):             # <<<<<<<<<<<<<<
 *             # forwards[:, s*k_endog:(s+1)*k_endog] = (
 *             #     np.dot(
 */
    __pyx_t_31 = __pyx_v_order;
    for (__pyx_t_32 = 0; __pyx_t_32 < __pyx_t_31; __pyx_t_32+=1) {
      __pyx_v_s = __pyx_t_32;

      /* "statsmodels\tsa\statespace\_statespace.pyx":3984
 * 
 *             # Get TF
 *             zcopy(&k_endog2, &forwards[s * k_endog2], &inc, &tmp2[0,0], &inc)             # <<<<<<<<<<<<<<
 *             ztrmm("L", "U", "T", "N", &k_endog, &k_endog,
 *               &alpha, &initial_variance[0, 0], &k_endog,
 */
      __pyx_t_133 = 0;
      __pyx_t_134 = 0;
      __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zcopy((&__pyx_v_k_endog2), (&(__pyx_v_forwards[(__pyx_v_s * __pyx_v_k_endog2)])), (&__pyx_v_inc), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_tmp2.data) + __pyx_t_133)) ) + __pyx_t_134 * __pyx_v_tmp2.strides[1]) )))), (&__pyx_v_inc));

      /* "statsmodels\tsa\statespace\_statespace.pyx":3986
 *             zcopy(&k_endog2, &forwards[s * k_endog2], &inc, &tmp2[0,0], &inc)
 *             ztrmm("L", "U", "T", "N", &k_endog, &k_endog,
 *               &alpha, &initial_variance[0, 0], &k_endog,             # <<<<<<<<<<<<<<
 *                       &tmp2[0, 0], &k_endog)
 *             for k in range(k_endog):
 */
      if (unlikely(!__pyx_v_initial_variance.memview)) { __Pyx_RaiseUnboundLocalError("initial_variance"); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 3986; __pyx_clineno = __LINE__; goto __pyx_L1_error;} }
      __pyx_t_135 = 0;
      __pyx_t_136 = 0;

      /* "statsmodels\tsa\statespace\_statespace.pyx":3987
 *             ztrmm("L", "U", "T", "N", &k_endog, &k_endog,
 *               &alpha, &initial_variance[0, 0], &k_endog,
 *                       &tmp2[0, 0], &k_endog)             # <<<<<<<<<<<<<<
 *             for k in range(k_endog):
 *                 zcopy(&k_endog, &tmp2[k,0], &k_endog, &tmp[0, k], &inc)
 */
      __pyx_t_137 = 0;
      __pyx_t_138 = 0;

      /* "statsmodels\tsa\statespace\_statespace.pyx":3985
 *             # Get TF
 *             zcopy(&k_endog2, &forwards[s * k_endog2], &inc, &tmp2[0,0], &inc)
 *             ztrmm("L", "U", "T", "N", &k_endog, &k_endog,             # <<<<<<<<<<<<<<
 *               &alpha, &initial_variance[0, 0], &k_endog,
 *                       &tmp2[0, 0], &k_endog)
 */
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      /* "statsmodels\tsa\statespace\_statespace.pyx":3988
 *               &alpha, &initial_variance[0, 0], &k_endog,
 *                       &tmp2[0, 0], &k_endog)
 *             for k in range(k_endog):             # <<<<<<<<<<<<<<
 *                 zcopy(&k_endog, &tmp2[k,0], &k_endog, &tmp[0, k], &inc)
 *             # Get x'
 */
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      for (__pyx_t_139 = 0; __pyx_t_139 < __pyx_t_50; __pyx_t_139+=1) {
        __pyx_v_k = __pyx_t_139;

        /* "statsmodels\tsa\statespace\_statespace.pyx":3989
 *                       &tmp2[0, 0], &k_endog)
 *             for k in range(k_endog):
 *                 zcopy(&k_endog, &tmp2[k,0], &k_endog, &tmp[0, k], &inc)             # <<<<<<<<<<<<<<
 *             # Get x'
 *             ztrtrs("U", "N", "N", &k_endog, &k_endog, &initial_variance[0,0], &k_endog,
 */
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        __pyx_t_141 = 0;
        __pyx_t_142 = 0;
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        __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_zcopy((&__pyx_v_k_endog), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_tmp2.data) + __pyx_t_140)) ) + __pyx_t_141 * __pyx_v_tmp2.strides[1]) )))), (&__pyx_v_k_endog), (&(*((__pyx_t_double_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_double_complex *) __pyx_v_tmp.data) + __pyx_t_142)) ) + __pyx_t_143 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_inc));
      }

      /* "statsmodels\tsa\statespace\_statespace.pyx":3991
 *                 zcopy(&k_endog, &tmp2[k,0], &k_endog, &tmp[0, k], &inc)
 *             # Get x'
 *             ztrtrs("U", "N", "N", &k_endog, &k_endog, &initial_variance[0,0], &k_endog,             # <<<<<<<<<<<<<<
 *                                                                &tmp[0, 0], &k_endog, &info)
 *             # Get x
 */
      if (unlikely(!__pyx_v_initial_variance.memview)) { __Pyx_RaiseUnboundLocalError("initial_variance"); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 3991; __pyx_clineno = __LINE__; goto __pyx_L1_error;} }
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      __pyx_t_145 = 0;

      /* "statsmodels\tsa\statespace\_statespace.pyx":3992
 *             # Get x'
 *             ztrtrs("U", "N", "N", &k_endog, &k_endog, &initial_variance[0,0], &k_endog,
 *                                                                &tmp[0, 0], &k_endog, &info)             # <<<<<<<<<<<<<<
 *             # Get x
 *             for k in range(k_endog):
 */
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      __pyx_t_147 = 0;

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 *                 zcopy(&k_endog, &tmp2[k,0], &k_endog, &tmp[0, k], &inc)
 *             # Get x'
 *             ztrtrs("U", "N", "N", &k_endog, &k_endog, &initial_variance[0,0], &k_endog,             # <<<<<<<<<<<<<<
 *                                                                &tmp[0, 0], &k_endog, &info)
 *             # Get x
 */
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      /* "statsmodels\tsa\statespace\_statespace.pyx":3994
 *                                                                &tmp[0, 0], &k_endog, &info)
 *             # Get x
 *             for k in range(k_endog):             # <<<<<<<<<<<<<<
 *                 zcopy(&k_endog, &tmp[k,0], &k_endog, &forwards[s * k_endog2 + k*k_endog], &inc)
 * 
 */
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        /* "statsmodels\tsa\statespace\_statespace.pyx":3995
 *             # Get x
 *             for k in range(k_endog):
 *                 zcopy(&k_endog, &tmp[k,0], &k_endog, &forwards[s * k_endog2 + k*k_endog], &inc)             # <<<<<<<<<<<<<<
 * 
 * 
 */
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    goto __pyx_L15;
  }
  __pyx_L15:;

  /* "statsmodels\tsa\statespace\_statespace.pyx":3998
 * 
 * 
 *     if order % 2 == 0:             # <<<<<<<<<<<<<<
 *         return forwards2, forward_variance
 *     else:
 */
  __pyx_t_3 = ((__Pyx_mod_long(__pyx_v_order, 2) == 0) != 0);
  if (__pyx_t_3) {

    /* "statsmodels\tsa\statespace\_statespace.pyx":3999
 * 
 *     if order % 2 == 0:
 *         return forwards2, forward_variance             # <<<<<<<<<<<<<<
 *     else:
 *         return forwards1, forward_variance
 */
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  /*else*/ {

    /* "statsmodels\tsa\statespace\_statespace.pyx":4001
 *         return forwards2, forward_variance
 *     else:
 *         return forwards1, forward_variance             # <<<<<<<<<<<<<<
 * 
 * cpdef _zconstrain_sv_less_than_one(np.complex128_t [::1,:] unconstrained, int order, int k_endog):
 */
    __Pyx_XDECREF(__pyx_r);
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 *         validate_vector_shape('state intercept', &self.state_intercept.shape[0],
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 *         validate_matrix_shape('transition', &self.transition.shape[0],             # <<<<<<<<<<<<<<
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 *                               self.k_states, self.nobs)
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 *         self.time_invariant = (
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 *             self.obs_intercept.shape[1] == 1    and             # <<<<<<<<<<<<<<
 *             self.obs_cov.shape[2] == 1          and
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 *             self.transition.shape[2] == 1       and
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 *             self.transition.shape[2] == 1       and             # <<<<<<<<<<<<<<
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 *             self.transition.shape[2] == 1       and
 *             self.state_intercept.shape[1] == 1  and             # <<<<<<<<<<<<<<
 *             self.selection.shape[2] == 1        and
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 *             self.transition.shape[2] == 1       and
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 *             self.selection.shape[2] == 1        and             # <<<<<<<<<<<<<<
 *             self.state_cov.shape[2] == 1
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 */
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 */
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 * 
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 *         # (we only allocate memory for time-varying array if necessary)
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 *             dim3[2] = self.nobs             # <<<<<<<<<<<<<<
 *         self.selected_state_cov = np.PyArray_ZEROS(3, dim3, np.NPY_FLOAT64, FORTRAN)
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 * 
 *         # Handle missing data
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 *         self.nmissing = np.array(np.sum(self.missing, axis=0), dtype=np.int32)
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 */
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  /* "statsmodels\tsa\statespace\_statespace.pyx":4380
 *             kfilter._forecast_error_cov[j + i*kfilter.k_endog] = 0
 * 
 * cdef int dupdating_missing_conventional(dKalmanFilter kfilter):             # <<<<<<<<<<<<<<
 *     cdef int inc = 1
 * 
 */

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 * 
 * cdef np.float64_t dinverse_missing_conventional(dKalmanFilter kfilter, np.float64_t determinant)  except *:             # <<<<<<<<<<<<<<
 *     # Since the inverse of the forecast error covariance matrix is not
 *     # stored, we don't need to fill it (e.g. with NPY_NAN values). Instead,
 */

static __pyx_t_5numpy_float64_t __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_dinverse_missing_conventional(CYTHON_UNUSED struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_kfilter, CYTHON_UNUSED __pyx_t_5numpy_float64_t __pyx_v_determinant) {
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 * 
 * cdef np.float64_t dloglikelihood_missing_conventional(dKalmanFilter kfilter, np.float64_t determinant):
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 * 
 * cdef np.float64_t dinverse_missing_conventional(dKalmanFilter kfilter, np.float64_t determinant)  except *:             # <<<<<<<<<<<<<<
 *     # Since the inverse of the forecast error covariance matrix is not
 *     # stored, we don't need to fill it (e.g. with NPY_NAN values). Instead,
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/* "statsmodels\tsa\statespace\_statespace.pyx":4394
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 * cdef np.float64_t dloglikelihood_missing_conventional(dKalmanFilter kfilter, np.float64_t determinant):             # <<<<<<<<<<<<<<
 *     return 0.0
 * 
 */

static __pyx_t_5numpy_float64_t __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_dloglikelihood_missing_conventional(CYTHON_UNUSED struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_kfilter, CYTHON_UNUSED __pyx_t_5numpy_float64_t __pyx_v_determinant) {
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 * cdef np.float64_t dloglikelihood_missing_conventional(dKalmanFilter kfilter, np.float64_t determinant):
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 * 
 * # ### Conventional Kalman filter
 */
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 *     return 0.0
 * 
 * cdef np.float64_t dloglikelihood_missing_conventional(dKalmanFilter kfilter, np.float64_t determinant):             # <<<<<<<<<<<<<<
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/* "statsmodels\tsa\statespace\_statespace.pyx":4404
 * # See Durbin and Koopman (2012) Chapter 4
 * 
 * cdef int dforecast_conventional(dKalmanFilter kfilter):             # <<<<<<<<<<<<<<
 * 
 *     # Constants
 */

static int __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_dforecast_conventional(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_kfilter) {
  int __pyx_v_inc;
  __pyx_t_5numpy_float64_t __pyx_v_alpha;
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 *         np.float64_t alpha = 1.0
 *         np.float64_t beta = 0.0
 */
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  /* "statsmodels\tsa\statespace\_statespace.pyx":4409
 *     cdef:
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 *         np.float64_t alpha = 1.0             # <<<<<<<<<<<<<<
 *         np.float64_t beta = 0.0
 *         np.float64_t gamma = -1.0
 */
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  /* "statsmodels\tsa\statespace\_statespace.pyx":4410
 *         int inc = 1, ld
 *         np.float64_t alpha = 1.0
 *         np.float64_t beta = 0.0             # <<<<<<<<<<<<<<
 *         np.float64_t gamma = -1.0
 * 
 */
  __pyx_v_beta = 0.0;

  /* "statsmodels\tsa\statespace\_statespace.pyx":4411
 *         np.float64_t alpha = 1.0
 *         np.float64_t beta = 0.0
 *         np.float64_t gamma = -1.0             # <<<<<<<<<<<<<<
 * 
 *     # #### Forecast for time t
 */
  __pyx_v_gamma = -1.0;

  /* "statsmodels\tsa\statespace\_statespace.pyx":4420
 * 
 *     # $\\# = d_t$
 *     dcopy(&kfilter.k_endog, kfilter._obs_intercept, &inc, kfilter._forecast, &inc)             # <<<<<<<<<<<<<<
 *     # `forecast` $= 1.0 * Z_t a_t + 1.0 * \\#$
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 */
  __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dcopy((&__pyx_v_kfilter->k_endog), __pyx_v_kfilter->_obs_intercept, (&__pyx_v_inc), __pyx_v_kfilter->_forecast, (&__pyx_v_inc));

  /* "statsmodels\tsa\statespace\_statespace.pyx":4423
 *     # `forecast` $= 1.0 * Z_t a_t + 1.0 * \\#$
 *     # $(p \times 1) = (p \times m) (m \times 1) + (p \times 1)$
 *     dgemv("N", &kfilter.k_endog, &kfilter.k_states,             # <<<<<<<<<<<<<<
 *           &alpha, kfilter._design, &kfilter.k_endog,
 *                   kfilter._input_state, &inc,
 */
  __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dgemv(__pyx_k_N, (&__pyx_v_kfilter->k_endog), (&__pyx_v_kfilter->k_states), (&__pyx_v_alpha), __pyx_v_kfilter->_design, (&__pyx_v_kfilter->k_endog), __pyx_v_kfilter->_input_state, (&__pyx_v_inc), (&__pyx_v_alpha), __pyx_v_kfilter->_forecast, (&__pyx_v_inc));

  /* "statsmodels\tsa\statespace\_statespace.pyx":4432
 * 
 *     # $\\# = y_t$
 *     dcopy(&kfilter.k_endog, kfilter._obs, &inc, kfilter._forecast_error, &inc)             # <<<<<<<<<<<<<<
 *     # $v_t = -1.0 * $ `forecast` $ + \\#$
 *     # $(p \times 1) = (p \times 1) + (p \times 1)$
 */
  __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dcopy((&__pyx_v_kfilter->k_endog), __pyx_v_kfilter->_obs, (&__pyx_v_inc), __pyx_v_kfilter->_forecast_error, (&__pyx_v_inc));

  /* "statsmodels\tsa\statespace\_statespace.pyx":4435
 *     # $v_t = -1.0 * $ `forecast` $ + \\#$
 *     # $(p \times 1) = (p \times 1) + (p \times 1)$
 *     daxpy(&kfilter.k_endog, &gamma, kfilter._forecast, &inc, kfilter._forecast_error, &inc)             # <<<<<<<<<<<<<<
 * 
 *     # *Intermediate calculation* (used just below and then once more)
 */
  __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_daxpy((&__pyx_v_kfilter->k_endog), (&__pyx_v_gamma), __pyx_v_kfilter->_forecast, (&__pyx_v_inc), __pyx_v_kfilter->_forecast_error, (&__pyx_v_inc));

  /* "statsmodels\tsa\statespace\_statespace.pyx":4441
 *     # $\\#_1 = P_t Z_t'$
 *     # $(m \times p) = (m \times m) (p \times m)'$
 *     dgemm("N", "T", &kfilter.k_states, &kfilter.k_endog, &kfilter.k_states,             # <<<<<<<<<<<<<<
 *           &alpha, kfilter._input_state_cov, &kfilter.k_states,
 *                   kfilter._design, &kfilter.k_endog,
 */
  __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dgemm(__pyx_k_N, __pyx_k_T, (&__pyx_v_kfilter->k_states), (&__pyx_v_kfilter->k_endog), (&__pyx_v_kfilter->k_states), (&__pyx_v_alpha), __pyx_v_kfilter->_input_state_cov, (&__pyx_v_kfilter->k_states), __pyx_v_kfilter->_design, (&__pyx_v_kfilter->k_endog), (&__pyx_v_beta), __pyx_v_kfilter->_tmp1, (&__pyx_v_kfilter->k_states));

  /* "statsmodels\tsa\statespace\_statespace.pyx":4451
 *     # *Note*: this and does nothing at all to `forecast_error_cov` if
 *     # converged == True
 *     if not kfilter.converged:             # <<<<<<<<<<<<<<
 *         # $\\# = H_t$
 *         dcopy(&kfilter.k_endog2, kfilter._obs_cov, &inc, kfilter._forecast_error_cov, &inc)
 */
  __pyx_t_1 = ((!(__pyx_v_kfilter->converged != 0)) != 0);
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    /* "statsmodels\tsa\statespace\_statespace.pyx":4453
 *     if not kfilter.converged:
 *         # $\\# = H_t$
 *         dcopy(&kfilter.k_endog2, kfilter._obs_cov, &inc, kfilter._forecast_error_cov, &inc)             # <<<<<<<<<<<<<<
 * 
 *         # $F_t = 1.0 * Z_t \\#_1 + 1.0 * \\#$
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    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dcopy((&__pyx_v_kfilter->k_endog2), __pyx_v_kfilter->_obs_cov, (&__pyx_v_inc), __pyx_v_kfilter->_forecast_error_cov, (&__pyx_v_inc));

    /* "statsmodels\tsa\statespace\_statespace.pyx":4456
 * 
 *         # $F_t = 1.0 * Z_t \\#_1 + 1.0 * \\#$
 *         dgemm("N", "N", &kfilter.k_endog, &kfilter.k_endog, &kfilter.k_states,             # <<<<<<<<<<<<<<
 *               &alpha, kfilter._design, &kfilter.k_endog,
 *                      kfilter._tmp1, &kfilter.k_states,
 */
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dgemm(__pyx_k_N, __pyx_k_N, (&__pyx_v_kfilter->k_endog), (&__pyx_v_kfilter->k_endog), (&__pyx_v_kfilter->k_states), (&__pyx_v_alpha), __pyx_v_kfilter->_design, (&__pyx_v_kfilter->k_endog), __pyx_v_kfilter->_tmp1, (&__pyx_v_kfilter->k_states), (&__pyx_v_alpha), __pyx_v_kfilter->_forecast_error_cov, (&__pyx_v_kfilter->k_endog));
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 *               &alpha, kfilter._forecast_error_cov, &kfilter.k_endog)
 * 
 *     return 0             # <<<<<<<<<<<<<<
 * 
 * cdef int dupdating_conventional(dKalmanFilter kfilter):
 */
  __pyx_r = 0;
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  /* "statsmodels\tsa\statespace\_statespace.pyx":4404
 * # See Durbin and Koopman (2012) Chapter 4
 * 
 * cdef int dforecast_conventional(dKalmanFilter kfilter):             # <<<<<<<<<<<<<<
 * 
 *     # Constants
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/* "statsmodels\tsa\statespace\_statespace.pyx":4463
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 * cdef int dupdating_conventional(dKalmanFilter kfilter):             # <<<<<<<<<<<<<<
 *     # Constants
 *     cdef:
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 *         np.float64_t beta = 0.0
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  /* "statsmodels\tsa\statespace\_statespace.pyx":4467
 *     cdef:
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 *         np.float64_t alpha = 1.0             # <<<<<<<<<<<<<<
 *         np.float64_t beta = 0.0
 *         np.float64_t gamma = -1.0
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  /* "statsmodels\tsa\statespace\_statespace.pyx":4468
 *         int inc = 1
 *         np.float64_t alpha = 1.0
 *         np.float64_t beta = 0.0             # <<<<<<<<<<<<<<
 *         np.float64_t gamma = -1.0
 * 
 */
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  /* "statsmodels\tsa\statespace\_statespace.pyx":4469
 *         np.float64_t alpha = 1.0
 *         np.float64_t beta = 0.0
 *         np.float64_t gamma = -1.0             # <<<<<<<<<<<<<<
 * 
 *     # #### Filtered state for time t
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 *     # $a_{t|t} = a_t + P_t Z_t' F_t^{-1} v_t$
 *     # $a_{t|t} = 1.0 * \\#_1 \\#_2 + 1.0 a_t$
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  /* "statsmodels\tsa\statespace\_statespace.pyx":4475
 *     # $a_{t|t} = 1.0 * \\#_1 \\#_2 + 1.0 a_t$
 *     dcopy(&kfilter.k_states, kfilter._input_state, &inc, kfilter._filtered_state, &inc)
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  /* "statsmodels\tsa\statespace\_statespace.pyx":4486
 *     # *Note*: this and does nothing at all to `filtered_state_cov` if
 *     # converged == True
 *     if not kfilter.converged:             # <<<<<<<<<<<<<<
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 * 
 */
  __pyx_t_1 = ((!(__pyx_v_kfilter->converged != 0)) != 0);
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    /* "statsmodels\tsa\statespace\_statespace.pyx":4487
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 *     if not kfilter.converged:
 *         dcopy(&kfilter.k_states2, kfilter._input_state_cov, &inc, kfilter._filtered_state_cov, &inc)             # <<<<<<<<<<<<<<
 * 
 *         # `tmp0` array used here, dimension $(m \times m)$
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    /* "statsmodels\tsa\statespace\_statespace.pyx":4492
 *         # $\\#_0 = 1.0 * \\#_1 \\#_3$
 *         # $(m \times m) = (m \times p) (p \times m)$
 *         dgemm("N", "N", &kfilter.k_states, &kfilter.k_states, &kfilter.k_endog,             # <<<<<<<<<<<<<<
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    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dgemm(__pyx_k_N, __pyx_k_N, (&__pyx_v_kfilter->k_states), (&__pyx_v_kfilter->k_states), (&__pyx_v_kfilter->k_endog), (&__pyx_v_alpha), __pyx_v_kfilter->_tmp1, (&__pyx_v_kfilter->k_states), __pyx_v_kfilter->_tmp3, (&__pyx_v_kfilter->k_endog), (&__pyx_v_beta), __pyx_v_kfilter->_tmp0, (&__pyx_v_kfilter->k_states));

    /* "statsmodels\tsa\statespace\_statespace.pyx":4499
 *         # $P_{t|t} = - 1.0 * \\# P_t + 1.0 * P_t$
 *         # $(m \times m) = (m \times m) (m \times m) + (m \times m)$
 *         dgemm("N", "N", &kfilter.k_states, &kfilter.k_states, &kfilter.k_states,             # <<<<<<<<<<<<<<
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 * 
 *     return 0             # <<<<<<<<<<<<<<
 * 
 * cdef int dprediction_conventional(dKalmanFilter kfilter):
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  /* "statsmodels\tsa\statespace\_statespace.pyx":4463
 *     return 0
 * 
 * cdef int dupdating_conventional(dKalmanFilter kfilter):             # <<<<<<<<<<<<<<
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/* "statsmodels\tsa\statespace\_statespace.pyx":4506
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 * cdef int dprediction_conventional(dKalmanFilter kfilter):             # <<<<<<<<<<<<<<
 * 
 *     # Constants
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 *         np.float64_t alpha = 1.0             # <<<<<<<<<<<<<<
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 *         np.float64_t gamma = -1.0
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 *         int inc = 1
 *         np.float64_t alpha = 1.0
 *         np.float64_t beta = 0.0             # <<<<<<<<<<<<<<
 *         np.float64_t gamma = -1.0
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 */
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 *         np.float64_t alpha = 1.0
 *         np.float64_t beta = 0.0
 *         np.float64_t gamma = -1.0             # <<<<<<<<<<<<<<
 * 
 *     # #### Predicted state for time t+1
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 *     # #### Predicted state for time t+1
 *     # $a_{t+1} = T_t a_{t|t} + c_t$
 *     dcopy(&kfilter.k_states, kfilter._state_intercept, &inc, kfilter._predicted_state, &inc)             # <<<<<<<<<<<<<<
 *     dgemv("N", &kfilter.k_states, &kfilter.k_states,
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 *         # Continue taking the inverse
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 */
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/* "statsmodels\tsa\statespace\_statespace.pyx":4777
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 *     if not kfilter.converged:
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      __pyx_v_obs_intercept_t = __pyx_v_t;
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 *             if self.model.design.shape[2] > 1:             design_t = t
 *             if self.model.obs_intercept.shape[1] > 1:      obs_intercept_t = t
 *             if self.model.obs_cov.shape[2] > 1:            obs_cov_t = t             # <<<<<<<<<<<<<<
 *             if self.model.transition.shape[2] > 1:         transition_t = t
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 */
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    /* "statsmodels\tsa\statespace\_statespace.pyx":5310
 *             if self.model.obs_intercept.shape[1] > 1:      obs_intercept_t = t
 *             if self.model.obs_cov.shape[2] > 1:            obs_cov_t = t
 *             if self.model.transition.shape[2] > 1:         transition_t = t             # <<<<<<<<<<<<<<
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 *             if self.model.obs_cov.shape[2] > 1:            obs_cov_t = t
 *             if self.model.transition.shape[2] > 1:         transition_t = t
 *             if self.model.state_intercept.shape[1] > 1:    state_intercept_t = t             # <<<<<<<<<<<<<<
 *             if self.model.selection.shape[2] > 1:          selection_t = t
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 *             if self.model.state_intercept.shape[1] > 1:    state_intercept_t = t
 *             if self.model.selection.shape[2] > 1:          selection_t = t             # <<<<<<<<<<<<<<
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 */
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    __pyx_t_6 = (((__pyx_v_self->model->selection.shape[2]) > 1) != 0);
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    /* "statsmodels\tsa\statespace\_statespace.pyx":5313
 *             if self.model.state_intercept.shape[1] > 1:    state_intercept_t = t
 *             if self.model.selection.shape[2] > 1:          selection_t = t
 *             if self.model.state_cov.shape[2] > 1:          state_cov_t = t             # <<<<<<<<<<<<<<
 * 
 *         # Initialize object-level pointers to statespace arrays
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 *         # Initialize object-level pointers to statespace arrays
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 *         self._design = &self.model.design[0, 0, design_t]
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 *         self._design = &self.model.design[0, 0, design_t]             # <<<<<<<<<<<<<<
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 *         self._design = &self.model.design[0, 0, design_t]
 *         self._obs_intercept = &self.model.obs_intercept[0, obs_intercept_t]             # <<<<<<<<<<<<<<
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 *         self._obs_intercept = &self.model.obs_intercept[0, obs_intercept_t]
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 *         self._obs_cov = &self.model.obs_cov[0, 0, obs_cov_t]
 *         self._transition = &self.model.transition[0, 0, transition_t]             # <<<<<<<<<<<<<<
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    if (unlikely(!__pyx_v_self->model->missing.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 5492; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
    __pyx_t_5 = __pyx_v_i;
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      /* "statsmodels\tsa\statespace\_statespace.pyx":5494
 *             if not self.model.missing[i, self.t]:
 * 
 *                 self.selected_obs[k] = self.model.obs[i, self.t]             # <<<<<<<<<<<<<<
 * 
 *                 # i is rows
 */
      if (unlikely(!__pyx_v_self->model->obs.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 5494; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
      __pyx_t_7 = __pyx_v_i;
      __pyx_t_8 = __pyx_v_self->t;
      if (unlikely(!__pyx_v_self->selected_obs.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 5494; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
      __pyx_t_9 = __pyx_v_k;
      *((__pyx_t_5numpy_float64_t *) ( /* dim=0 */ (__pyx_v_self->selected_obs.data + __pyx_t_9 * __pyx_v_self->selected_obs.strides[0]) )) = (*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_self->model->obs.data) + __pyx_t_7)) ) + __pyx_t_8 * __pyx_v_self->model->obs.strides[1]) )));

      /* "statsmodels\tsa\statespace\_statespace.pyx":5499
 *                 # k is rows
 *                 dcopy(&self.model.k_states,
 *                       &self.model.design[i, 0, design_t], &self.model.k_endog,             # <<<<<<<<<<<<<<
 *                       &self.selected_design[k], &self.k_endog)
 * 
 */
      if (unlikely(!__pyx_v_self->model->design.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 5499; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
      __pyx_t_10 = __pyx_v_i;
      __pyx_t_11 = 0;
      __pyx_t_12 = __pyx_v_design_t;

      /* "statsmodels\tsa\statespace\_statespace.pyx":5500
 *                 dcopy(&self.model.k_states,
 *                       &self.model.design[i, 0, design_t], &self.model.k_endog,
 *                       &self.selected_design[k], &self.k_endog)             # <<<<<<<<<<<<<<
 * 
 *                 # i, k is columns
 */
      if (unlikely(!__pyx_v_self->selected_design.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 5500; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
      __pyx_t_13 = __pyx_v_k;

      /* "statsmodels\tsa\statespace\_statespace.pyx":5498
 *                 # i is rows
 *                 # k is rows
 *                 dcopy(&self.model.k_states,             # <<<<<<<<<<<<<<
 *                       &self.model.design[i, 0, design_t], &self.model.k_endog,
 *                       &self.selected_design[k], &self.k_endog)
 */
      __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dcopy((&__pyx_v_self->model->k_states), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=2 */ (( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_self->model->design.data) + __pyx_t_10)) ) + __pyx_t_11 * __pyx_v_self->model->design.strides[1]) ) + __pyx_t_12 * __pyx_v_self->model->design.strides[2]) )))), (&__pyx_v_self->model->k_endog), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=0 */ (__pyx_v_self->selected_design.data + __pyx_t_13 * __pyx_v_self->selected_design.strides[0]) )))), (&__pyx_v_self->k_endog));

      /* "statsmodels\tsa\statespace\_statespace.pyx":5504
 *                 # i, k is columns
 *                 # j, l is rows
 *                 l = 0             # <<<<<<<<<<<<<<
 *                 for j in range(self.model.k_endog):
 *                     if not self.model.missing[j, self.t]:
 */
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      /* "statsmodels\tsa\statespace\_statespace.pyx":5505
 *                 # j, l is rows
 *                 l = 0
 *                 for j in range(self.model.k_endog):             # <<<<<<<<<<<<<<
 *                     if not self.model.missing[j, self.t]:
 *                         self.selected_obs_cov[l + k*self.k_endog] = self.model.obs_cov[j, i, obs_cov_t]
 */
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        /* "statsmodels\tsa\statespace\_statespace.pyx":5506
 *                 l = 0
 *                 for j in range(self.model.k_endog):
 *                     if not self.model.missing[j, self.t]:             # <<<<<<<<<<<<<<
 *                         self.selected_obs_cov[l + k*self.k_endog] = self.model.obs_cov[j, i, obs_cov_t]
 *                         l += 1
 */
        if (unlikely(!__pyx_v_self->model->missing.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 5506; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
        __pyx_t_16 = __pyx_v_j;
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          /* "statsmodels\tsa\statespace\_statespace.pyx":5507
 *                 for j in range(self.model.k_endog):
 *                     if not self.model.missing[j, self.t]:
 *                         self.selected_obs_cov[l + k*self.k_endog] = self.model.obs_cov[j, i, obs_cov_t]             # <<<<<<<<<<<<<<
 *                         l += 1
 *                 k += 1
 */
          if (unlikely(!__pyx_v_self->model->obs_cov.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 5507; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
          __pyx_t_18 = __pyx_v_j;
          __pyx_t_19 = __pyx_v_i;
          __pyx_t_20 = __pyx_v_obs_cov_t;
          if (unlikely(!__pyx_v_self->selected_obs_cov.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 5507; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
          __pyx_t_21 = (__pyx_v_l + (__pyx_v_k * __pyx_v_self->k_endog));
          *((__pyx_t_5numpy_float64_t *) ( /* dim=0 */ (__pyx_v_self->selected_obs_cov.data + __pyx_t_21 * __pyx_v_self->selected_obs_cov.strides[0]) )) = (*((__pyx_t_5numpy_float64_t *) ( /* dim=2 */ (( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_self->model->obs_cov.data) + __pyx_t_18)) ) + __pyx_t_19 * __pyx_v_self->model->obs_cov.strides[1]) ) + __pyx_t_20 * __pyx_v_self->model->obs_cov.strides[2]) )));

          /* "statsmodels\tsa\statespace\_statespace.pyx":5508
 *                     if not self.model.missing[j, self.t]:
 *                         self.selected_obs_cov[l + k*self.k_endog] = self.model.obs_cov[j, i, obs_cov_t]
 *                         l += 1             # <<<<<<<<<<<<<<
 *                 k += 1
 *         self._obs = &self.selected_obs[0]
 */
          __pyx_v_l = (__pyx_v_l + 1);
          goto __pyx_L10;
        }
        __pyx_L10:;
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      /* "statsmodels\tsa\statespace\_statespace.pyx":5509
 *                         self.selected_obs_cov[l + k*self.k_endog] = self.model.obs_cov[j, i, obs_cov_t]
 *                         l += 1
 *                 k += 1             # <<<<<<<<<<<<<<
 *         self._obs = &self.selected_obs[0]
 *         self._design = &self.selected_design[0]
 */
      __pyx_v_k = (__pyx_v_k + 1);
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  /* "statsmodels\tsa\statespace\_statespace.pyx":5510
 *                         l += 1
 *                 k += 1
 *         self._obs = &self.selected_obs[0]             # <<<<<<<<<<<<<<
 *         self._design = &self.selected_design[0]
 *         self._obs_cov = &self.selected_obs_cov[0]
 */
  if (unlikely(!__pyx_v_self->selected_obs.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 5510; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
  __pyx_t_22 = 0;
  __pyx_v_self->_obs = (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=0 */ (__pyx_v_self->selected_obs.data + __pyx_t_22 * __pyx_v_self->selected_obs.strides[0]) ))));

  /* "statsmodels\tsa\statespace\_statespace.pyx":5511
 *                 k += 1
 *         self._obs = &self.selected_obs[0]
 *         self._design = &self.selected_design[0]             # <<<<<<<<<<<<<<
 *         self._obs_cov = &self.selected_obs_cov[0]
 * 
 */
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  __pyx_t_23 = 0;
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  /* "statsmodels\tsa\statespace\_statespace.pyx":5512
 *         self._obs = &self.selected_obs[0]
 *         self._design = &self.selected_design[0]
 *         self._obs_cov = &self.selected_obs_cov[0]             # <<<<<<<<<<<<<<
 * 
 *     cdef void post_convergence(self):
 */
  if (unlikely(!__pyx_v_self->selected_obs_cov.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 5512; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
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  /* "statsmodels\tsa\statespace\_statespace.pyx":5472
 *         # filter
 * 
 *     cdef void _select_missing_partial_obs(self):             # <<<<<<<<<<<<<<
 *         cdef:
 *             int i, j, k, l
 */

  /* function exit code */
  goto __pyx_L0;
  __pyx_L1_error:;
  __Pyx_WriteUnraisable("statsmodels.tsa.statespace._statespace.dKalmanFilter._select_missing_partial_obs", __pyx_clineno, __pyx_lineno, __pyx_filename, 0);
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/* "statsmodels\tsa\statespace\_statespace.pyx":5514
 *         self._obs_cov = &self.selected_obs_cov[0]
 * 
 *     cdef void post_convergence(self):             # <<<<<<<<<<<<<<
 *         # TODO this should probably be defined separately for each Kalman filter type - e.g. `post_convergence_conventional`, etc.
 * 
 */

static void __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_post_convergence(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self) {
  int __pyx_v_inc;
  __Pyx_RefNannyDeclarations
  int __pyx_t_1;
  __pyx_t_5numpy_float64_t __pyx_t_2;
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  /* "statsmodels\tsa\statespace\_statespace.pyx":5519
 *         # Constants
 *         cdef:
 *             int inc = 1             # <<<<<<<<<<<<<<
 * 
 *         if self.converged:
 */
  __pyx_v_inc = 1;

  /* "statsmodels\tsa\statespace\_statespace.pyx":5521
 *             int inc = 1
 * 
 *         if self.converged:             # <<<<<<<<<<<<<<
 *             # $F_t$
 *             dcopy(&self.k_endog2, self._converged_forecast_error_cov, &inc, self._forecast_error_cov, &inc)
 */
  __pyx_t_1 = (__pyx_v_self->converged != 0);
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    /* "statsmodels\tsa\statespace\_statespace.pyx":5523
 *         if self.converged:
 *             # $F_t$
 *             dcopy(&self.k_endog2, self._converged_forecast_error_cov, &inc, self._forecast_error_cov, &inc)             # <<<<<<<<<<<<<<
 *             # $P_{t|t}$
 *             dcopy(&self.k_states2, self._converged_filtered_state_cov, &inc, self._filtered_state_cov, &inc)
 */
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dcopy((&__pyx_v_self->k_endog2), __pyx_v_self->_converged_forecast_error_cov, (&__pyx_v_inc), __pyx_v_self->_forecast_error_cov, (&__pyx_v_inc));

    /* "statsmodels\tsa\statespace\_statespace.pyx":5525
 *             dcopy(&self.k_endog2, self._converged_forecast_error_cov, &inc, self._forecast_error_cov, &inc)
 *             # $P_{t|t}$
 *             dcopy(&self.k_states2, self._converged_filtered_state_cov, &inc, self._filtered_state_cov, &inc)             # <<<<<<<<<<<<<<
 *             # $P_t$
 *             dcopy(&self.k_states2, self._converged_predicted_state_cov, &inc, self._predicted_state_cov, &inc)
 */
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dcopy((&__pyx_v_self->k_states2), __pyx_v_self->_converged_filtered_state_cov, (&__pyx_v_inc), __pyx_v_self->_filtered_state_cov, (&__pyx_v_inc));

    /* "statsmodels\tsa\statespace\_statespace.pyx":5527
 *             dcopy(&self.k_states2, self._converged_filtered_state_cov, &inc, self._filtered_state_cov, &inc)
 *             # $P_t$
 *             dcopy(&self.k_states2, self._converged_predicted_state_cov, &inc, self._predicted_state_cov, &inc)             # <<<<<<<<<<<<<<
 *             # $|F_t|$
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 */
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dcopy((&__pyx_v_self->k_states2), __pyx_v_self->_converged_predicted_state_cov, (&__pyx_v_inc), __pyx_v_self->_predicted_state_cov, (&__pyx_v_inc));

    /* "statsmodels\tsa\statespace\_statespace.pyx":5529
 *             dcopy(&self.k_states2, self._converged_predicted_state_cov, &inc, self._predicted_state_cov, &inc)
 *             # $|F_t|$
 *             self.determinant = self.converged_determinant             # <<<<<<<<<<<<<<
 * 
 *     cdef void numerical_stability(self):
 */
    __pyx_t_2 = __pyx_v_self->converged_determinant;
    __pyx_v_self->determinant = __pyx_t_2;
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  __pyx_L3:;

  /* "statsmodels\tsa\statespace\_statespace.pyx":5514
 *         self._obs_cov = &self.selected_obs_cov[0]
 * 
 *     cdef void post_convergence(self):             # <<<<<<<<<<<<<<
 *         # TODO this should probably be defined separately for each Kalman filter type - e.g. `post_convergence_conventional`, etc.
 * 
 */

  /* function exit code */
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/* "statsmodels\tsa\statespace\_statespace.pyx":5531
 *             self.determinant = self.converged_determinant
 * 
 *     cdef void numerical_stability(self):             # <<<<<<<<<<<<<<
 *         cdef int i, j
 *         cdef int predicted_t = self.t
 */

static void __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_numerical_stability(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self) {
  int __pyx_v_i;
  int __pyx_v_j;
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  __pyx_t_5numpy_float64_t __pyx_v_value;
  __Pyx_RefNannyDeclarations
  int __pyx_t_1;
  int __pyx_t_2;
  int __pyx_t_3;
  int __pyx_t_4;
  int __pyx_t_5;
  int __pyx_t_6;
  int __pyx_t_7;
  long __pyx_t_8;
  int __pyx_t_9;
  int __pyx_t_10;
  long __pyx_t_11;
  int __pyx_t_12;
  int __pyx_t_13;
  long __pyx_t_14;
  int __pyx_t_15;
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  /* "statsmodels\tsa\statespace\_statespace.pyx":5533
 *     cdef void numerical_stability(self):
 *         cdef int i, j
 *         cdef int predicted_t = self.t             # <<<<<<<<<<<<<<
 *         cdef np.float64_t value
 * 
 */
  __pyx_t_1 = __pyx_v_self->t;
  __pyx_v_predicted_t = __pyx_t_1;

  /* "statsmodels\tsa\statespace\_statespace.pyx":5536
 *         cdef np.float64_t value
 * 
 *         if self.conserve_memory & MEMORY_NO_PREDICTED:             # <<<<<<<<<<<<<<
 *             predicted_t = 1
 * 
 */
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    /* "statsmodels\tsa\statespace\_statespace.pyx":5537
 * 
 *         if self.conserve_memory & MEMORY_NO_PREDICTED:
 *             predicted_t = 1             # <<<<<<<<<<<<<<
 * 
 *         if self.stability_method & STABILITY_FORCE_SYMMETRY:
 */
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  __pyx_L3:;

  /* "statsmodels\tsa\statespace\_statespace.pyx":5539
 *             predicted_t = 1
 * 
 *         if self.stability_method & STABILITY_FORCE_SYMMETRY:             # <<<<<<<<<<<<<<
 *             # Enforce symmetry of predicted covariance matrix
 *             # $P_{t+1} = 0.5 * (P_{t+1} + P_{t+1}')$
 */
  __pyx_t_2 = ((__pyx_v_self->stability_method & __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_STABILITY_FORCE_SYMMETRY) != 0);
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    /* "statsmodels\tsa\statespace\_statespace.pyx":5543
 *             # $P_{t+1} = 0.5 * (P_{t+1} + P_{t+1}')$
 *             # See Grewal (2001), Section 6.3.1.1
 *             for i in range(self.k_states):             # <<<<<<<<<<<<<<
 *                 for j in range(i, self.k_states):
 *                     value = 0.5 * (
 */
    __pyx_t_1 = __pyx_v_self->k_states;
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      /* "statsmodels\tsa\statespace\_statespace.pyx":5544
 *             # See Grewal (2001), Section 6.3.1.1
 *             for i in range(self.k_states):
 *                 for j in range(i, self.k_states):             # <<<<<<<<<<<<<<
 *                     value = 0.5 * (
 *                         self.predicted_state_cov[i,j,predicted_t+1] +
 */
      __pyx_t_4 = __pyx_v_self->k_states;
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        /* "statsmodels\tsa\statespace\_statespace.pyx":5546
 *                 for j in range(i, self.k_states):
 *                     value = 0.5 * (
 *                         self.predicted_state_cov[i,j,predicted_t+1] +             # <<<<<<<<<<<<<<
 *                         self.predicted_state_cov[j,i,predicted_t+1]
 *                     )
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        __pyx_t_6 = __pyx_v_i;
        __pyx_t_7 = __pyx_v_j;
        __pyx_t_8 = (__pyx_v_predicted_t + 1);

        /* "statsmodels\tsa\statespace\_statespace.pyx":5547
 *                     value = 0.5 * (
 *                         self.predicted_state_cov[i,j,predicted_t+1] +
 *                         self.predicted_state_cov[j,i,predicted_t+1]             # <<<<<<<<<<<<<<
 *                     )
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 */
        if (unlikely(!__pyx_v_self->predicted_state_cov.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 5547; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
        __pyx_t_9 = __pyx_v_j;
        __pyx_t_10 = __pyx_v_i;
        __pyx_t_11 = (__pyx_v_predicted_t + 1);

        /* "statsmodels\tsa\statespace\_statespace.pyx":5545
 *             for i in range(self.k_states):
 *                 for j in range(i, self.k_states):
 *                     value = 0.5 * (             # <<<<<<<<<<<<<<
 *                         self.predicted_state_cov[i,j,predicted_t+1] +
 *                         self.predicted_state_cov[j,i,predicted_t+1]
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 *                     self.predicted_state_cov[j,i,predicted_t+1] = value
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 *                     self.predicted_state_cov[i,j,predicted_t+1] = value
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 *     cdef void check_convergence(self):
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 *     cdef void numerical_stability(self):             # <<<<<<<<<<<<<<
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 *     cdef void check_convergence(self):             # <<<<<<<<<<<<<<
 *         # Constants
 *         cdef:
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static void __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_check_convergence(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self) {
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 *             int filtered_t = self.t
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 *             int filtered_t = self.t             # <<<<<<<<<<<<<<
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 *             int filtered_t = self.t
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 *             int filtered_t = self.t
 *             int predicted_t = self.t
 *         if self.conserve_memory & MEMORY_NO_FORECAST > 0:             # <<<<<<<<<<<<<<
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 *             int predicted_t = self.t
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 *         if self.conserve_memory & MEMORY_NO_FILTERED > 0:             # <<<<<<<<<<<<<<
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 */
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 *             forecast_t = 1
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  /* "statsmodels\tsa\statespace\_statespace.pyx":5568
 *         if self.conserve_memory & MEMORY_NO_FILTERED > 0:
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 *         if self.conserve_memory & MEMORY_NO_PREDICTED > 0:             # <<<<<<<<<<<<<<
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 */
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    /* "statsmodels\tsa\statespace\_statespace.pyx":5569
 *             filtered_t = 1
 *         if self.conserve_memory & MEMORY_NO_PREDICTED > 0:
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 * 
 *         if self.time_invariant and not self.converged and self.model.nmissing[self.t] == 0:
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 *             predicted_t = 1
 * 
 *         if self.time_invariant and not self.converged and self.model.nmissing[self.t] == 0:             # <<<<<<<<<<<<<<
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 *             #
 */
  __pyx_t_3 = (__pyx_v_self->time_invariant != 0);
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  } else {
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    goto __pyx_L7_bool_binop_done;
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  if (unlikely(!__pyx_v_self->model->nmissing.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 5571; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
  __pyx_t_1 = __pyx_v_self->t;
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    /* "statsmodels\tsa\statespace\_statespace.pyx":5576
 *             # `tmp0` array used here, dimension $(m \times m)$
 *             # `tmp1` array used here, dimension $(1 \times 1)$
 *             dcopy(&self.k_states2, self._input_state_cov, &inc, self._tmp0, &inc)             # <<<<<<<<<<<<<<
 *             daxpy(&self.k_states2, &gamma, self._predicted_state_cov, &inc, self._tmp0, &inc)
 * 
 */
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    /* "statsmodels\tsa\statespace\_statespace.pyx":5577
 *             # `tmp1` array used here, dimension $(1 \times 1)$
 *             dcopy(&self.k_states2, self._input_state_cov, &inc, self._tmp0, &inc)
 *             daxpy(&self.k_states2, &gamma, self._predicted_state_cov, &inc, self._tmp0, &inc)             # <<<<<<<<<<<<<<
 * 
 *             if ddot(&self.k_states2, self._tmp0, &inc, self._tmp0, &inc) < self.tolerance:
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    /* "statsmodels\tsa\statespace\_statespace.pyx":5579
 *             daxpy(&self.k_states2, &gamma, self._predicted_state_cov, &inc, self._tmp0, &inc)
 * 
 *             if ddot(&self.k_states2, self._tmp0, &inc, self._tmp0, &inc) < self.tolerance:             # <<<<<<<<<<<<<<
 *                 self.converged = 1
 *                 self.period_converged = self.t
 */
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      /* "statsmodels\tsa\statespace\_statespace.pyx":5580
 * 
 *             if ddot(&self.k_states2, self._tmp0, &inc, self._tmp0, &inc) < self.tolerance:
 *                 self.converged = 1             # <<<<<<<<<<<<<<
 *                 self.period_converged = self.t
 * 
 */
      __pyx_v_self->converged = 1;

      /* "statsmodels\tsa\statespace\_statespace.pyx":5581
 *             if ddot(&self.k_states2, self._tmp0, &inc, self._tmp0, &inc) < self.tolerance:
 *                 self.converged = 1
 *                 self.period_converged = self.t             # <<<<<<<<<<<<<<
 * 
 * 
 */
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      __pyx_v_self->period_converged = __pyx_t_4;
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    __pyx_L10:;

    /* "statsmodels\tsa\statespace\_statespace.pyx":5586
 *             # If we just converged, copy the current iteration matrices to the
 *             # converged storage
 *             if self.converged == 1:             # <<<<<<<<<<<<<<
 *                 # $F_t$
 *                 dcopy(&self.k_endog2, &self.forecast_error_cov[0, 0, forecast_t], &inc, self._converged_forecast_error_cov, &inc)
 */
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      /* "statsmodels\tsa\statespace\_statespace.pyx":5588
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 *                 # $P_{t|t}$
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 *                     self.predicted_state_cov[j,i,predicted_t+1] = value
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 *     cdef void check_convergence(self):             # <<<<<<<<<<<<<<
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/* "statsmodels\tsa\statespace\_statespace.pyx":5596
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static void __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_migrate_storage(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *__pyx_v_self) {
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  Py_ssize_t __pyx_t_40;
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  Py_ssize_t __pyx_t_42;
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  /* "statsmodels\tsa\statespace\_statespace.pyx":5597
 * 
 *     cdef void migrate_storage(self):
 *         cdef int inc = 1             # <<<<<<<<<<<<<<
 * 
 *         # Forecast: 1 -> 0
 */
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  /* "statsmodels\tsa\statespace\_statespace.pyx":5600
 * 
 *         # Forecast: 1 -> 0
 *         if self.conserve_memory & MEMORY_NO_FORECAST > 0:             # <<<<<<<<<<<<<<
 *             dcopy(&self.k_endog, &self.forecast[0, 1], &inc, &self.forecast[0, 0], &inc)
 *             dcopy(&self.k_endog, &self.forecast_error[0, 1], &inc, &self.forecast_error[0, 0], &inc)
 */
  __pyx_t_1 = (((__pyx_v_self->conserve_memory & __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_MEMORY_NO_FORECAST) > 0) != 0);
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    /* "statsmodels\tsa\statespace\_statespace.pyx":5601
 *         # Forecast: 1 -> 0
 *         if self.conserve_memory & MEMORY_NO_FORECAST > 0:
 *             dcopy(&self.k_endog, &self.forecast[0, 1], &inc, &self.forecast[0, 0], &inc)             # <<<<<<<<<<<<<<
 *             dcopy(&self.k_endog, &self.forecast_error[0, 1], &inc, &self.forecast_error[0, 0], &inc)
 *             dcopy(&self.k_endog2, &self.forecast_error_cov[0, 0, 1], &inc, &self.forecast_error_cov[0, 0, 0], &inc)
 */
    if (unlikely(!__pyx_v_self->forecast.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 5601; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
    __pyx_t_2 = 0;
    __pyx_t_3 = 1;
    if (unlikely(!__pyx_v_self->forecast.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 5601; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
    __pyx_t_4 = 0;
    __pyx_t_5 = 0;
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dcopy((&__pyx_v_self->k_endog), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_self->forecast.data) + __pyx_t_2)) ) + __pyx_t_3 * __pyx_v_self->forecast.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_self->forecast.data) + __pyx_t_4)) ) + __pyx_t_5 * __pyx_v_self->forecast.strides[1]) )))), (&__pyx_v_inc));

    /* "statsmodels\tsa\statespace\_statespace.pyx":5602
 *         if self.conserve_memory & MEMORY_NO_FORECAST > 0:
 *             dcopy(&self.k_endog, &self.forecast[0, 1], &inc, &self.forecast[0, 0], &inc)
 *             dcopy(&self.k_endog, &self.forecast_error[0, 1], &inc, &self.forecast_error[0, 0], &inc)             # <<<<<<<<<<<<<<
 *             dcopy(&self.k_endog2, &self.forecast_error_cov[0, 0, 1], &inc, &self.forecast_error_cov[0, 0, 0], &inc)
 * 
 */
    if (unlikely(!__pyx_v_self->forecast_error.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 5602; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
    __pyx_t_6 = 0;
    __pyx_t_7 = 1;
    if (unlikely(!__pyx_v_self->forecast_error.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 5602; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
    __pyx_t_8 = 0;
    __pyx_t_9 = 0;
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dcopy((&__pyx_v_self->k_endog), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_self->forecast_error.data) + __pyx_t_6)) ) + __pyx_t_7 * __pyx_v_self->forecast_error.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_self->forecast_error.data) + __pyx_t_8)) ) + __pyx_t_9 * __pyx_v_self->forecast_error.strides[1]) )))), (&__pyx_v_inc));

    /* "statsmodels\tsa\statespace\_statespace.pyx":5603
 *             dcopy(&self.k_endog, &self.forecast[0, 1], &inc, &self.forecast[0, 0], &inc)
 *             dcopy(&self.k_endog, &self.forecast_error[0, 1], &inc, &self.forecast_error[0, 0], &inc)
 *             dcopy(&self.k_endog2, &self.forecast_error_cov[0, 0, 1], &inc, &self.forecast_error_cov[0, 0, 0], &inc)             # <<<<<<<<<<<<<<
 * 
 *         # Filtered: 1 -> 0
 */
    if (unlikely(!__pyx_v_self->forecast_error_cov.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 5603; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
    __pyx_t_10 = 0;
    __pyx_t_11 = 0;
    __pyx_t_12 = 1;
    if (unlikely(!__pyx_v_self->forecast_error_cov.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 5603; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
    __pyx_t_13 = 0;
    __pyx_t_14 = 0;
    __pyx_t_15 = 0;
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dcopy((&__pyx_v_self->k_endog2), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=2 */ (( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_self->forecast_error_cov.data) + __pyx_t_10)) ) + __pyx_t_11 * __pyx_v_self->forecast_error_cov.strides[1]) ) + __pyx_t_12 * __pyx_v_self->forecast_error_cov.strides[2]) )))), (&__pyx_v_inc), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=2 */ (( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_self->forecast_error_cov.data) + __pyx_t_13)) ) + __pyx_t_14 * __pyx_v_self->forecast_error_cov.strides[1]) ) + __pyx_t_15 * __pyx_v_self->forecast_error_cov.strides[2]) )))), (&__pyx_v_inc));
    goto __pyx_L3;
  }
  __pyx_L3:;

  /* "statsmodels\tsa\statespace\_statespace.pyx":5606
 * 
 *         # Filtered: 1 -> 0
 *         if self.conserve_memory & MEMORY_NO_FILTERED > 0:             # <<<<<<<<<<<<<<
 *             dcopy(&self.k_states, &self.filtered_state[0, 1], &inc, &self.filtered_state[0, 0], &inc)
 *             dcopy(&self.k_states2, &self.filtered_state_cov[0, 0, 1], &inc, &self.filtered_state_cov[0, 0, 0], &inc)
 */
  __pyx_t_1 = (((__pyx_v_self->conserve_memory & __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_MEMORY_NO_FILTERED) > 0) != 0);
  if (__pyx_t_1) {

    /* "statsmodels\tsa\statespace\_statespace.pyx":5607
 *         # Filtered: 1 -> 0
 *         if self.conserve_memory & MEMORY_NO_FILTERED > 0:
 *             dcopy(&self.k_states, &self.filtered_state[0, 1], &inc, &self.filtered_state[0, 0], &inc)             # <<<<<<<<<<<<<<
 *             dcopy(&self.k_states2, &self.filtered_state_cov[0, 0, 1], &inc, &self.filtered_state_cov[0, 0, 0], &inc)
 * 
 */
    if (unlikely(!__pyx_v_self->filtered_state.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 5607; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
    __pyx_t_16 = 0;
    __pyx_t_17 = 1;
    if (unlikely(!__pyx_v_self->filtered_state.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 5607; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
    __pyx_t_18 = 0;
    __pyx_t_19 = 0;
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dcopy((&__pyx_v_self->k_states), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_self->filtered_state.data) + __pyx_t_16)) ) + __pyx_t_17 * __pyx_v_self->filtered_state.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_self->filtered_state.data) + __pyx_t_18)) ) + __pyx_t_19 * __pyx_v_self->filtered_state.strides[1]) )))), (&__pyx_v_inc));

    /* "statsmodels\tsa\statespace\_statespace.pyx":5608
 *         if self.conserve_memory & MEMORY_NO_FILTERED > 0:
 *             dcopy(&self.k_states, &self.filtered_state[0, 1], &inc, &self.filtered_state[0, 0], &inc)
 *             dcopy(&self.k_states2, &self.filtered_state_cov[0, 0, 1], &inc, &self.filtered_state_cov[0, 0, 0], &inc)             # <<<<<<<<<<<<<<
 * 
 *         # Predicted: 1 -> 0
 */
    if (unlikely(!__pyx_v_self->filtered_state_cov.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 5608; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
    __pyx_t_20 = 0;
    __pyx_t_21 = 0;
    __pyx_t_22 = 1;
    if (unlikely(!__pyx_v_self->filtered_state_cov.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 5608; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
    __pyx_t_23 = 0;
    __pyx_t_24 = 0;
    __pyx_t_25 = 0;
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dcopy((&__pyx_v_self->k_states2), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=2 */ (( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_self->filtered_state_cov.data) + __pyx_t_20)) ) + __pyx_t_21 * __pyx_v_self->filtered_state_cov.strides[1]) ) + __pyx_t_22 * __pyx_v_self->filtered_state_cov.strides[2]) )))), (&__pyx_v_inc), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=2 */ (( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_self->filtered_state_cov.data) + __pyx_t_23)) ) + __pyx_t_24 * __pyx_v_self->filtered_state_cov.strides[1]) ) + __pyx_t_25 * __pyx_v_self->filtered_state_cov.strides[2]) )))), (&__pyx_v_inc));
    goto __pyx_L4;
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  __pyx_L4:;

  /* "statsmodels\tsa\statespace\_statespace.pyx":5611
 * 
 *         # Predicted: 1 -> 0
 *         if self.conserve_memory & MEMORY_NO_PREDICTED > 0:             # <<<<<<<<<<<<<<
 *             dcopy(&self.k_states, &self.predicted_state[0, 1], &inc, &self.predicted_state[0, 0], &inc)
 *             dcopy(&self.k_states2, &self.predicted_state_cov[0, 0, 1], &inc, &self.predicted_state_cov[0, 0, 0], &inc)
 */
  __pyx_t_1 = (((__pyx_v_self->conserve_memory & __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_MEMORY_NO_PREDICTED) > 0) != 0);
  if (__pyx_t_1) {

    /* "statsmodels\tsa\statespace\_statespace.pyx":5612
 *         # Predicted: 1 -> 0
 *         if self.conserve_memory & MEMORY_NO_PREDICTED > 0:
 *             dcopy(&self.k_states, &self.predicted_state[0, 1], &inc, &self.predicted_state[0, 0], &inc)             # <<<<<<<<<<<<<<
 *             dcopy(&self.k_states2, &self.predicted_state_cov[0, 0, 1], &inc, &self.predicted_state_cov[0, 0, 0], &inc)
 * 
 */
    if (unlikely(!__pyx_v_self->predicted_state.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 5612; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
    __pyx_t_26 = 0;
    __pyx_t_27 = 1;
    if (unlikely(!__pyx_v_self->predicted_state.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 5612; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
    __pyx_t_28 = 0;
    __pyx_t_29 = 0;
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dcopy((&__pyx_v_self->k_states), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_self->predicted_state.data) + __pyx_t_26)) ) + __pyx_t_27 * __pyx_v_self->predicted_state.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_self->predicted_state.data) + __pyx_t_28)) ) + __pyx_t_29 * __pyx_v_self->predicted_state.strides[1]) )))), (&__pyx_v_inc));

    /* "statsmodels\tsa\statespace\_statespace.pyx":5613
 *         if self.conserve_memory & MEMORY_NO_PREDICTED > 0:
 *             dcopy(&self.k_states, &self.predicted_state[0, 1], &inc, &self.predicted_state[0, 0], &inc)
 *             dcopy(&self.k_states2, &self.predicted_state_cov[0, 0, 1], &inc, &self.predicted_state_cov[0, 0, 0], &inc)             # <<<<<<<<<<<<<<
 * 
 *             # Predicted: 2 -> 1
 */
    if (unlikely(!__pyx_v_self->predicted_state_cov.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 5613; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
    __pyx_t_30 = 0;
    __pyx_t_31 = 0;
    __pyx_t_32 = 1;
    if (unlikely(!__pyx_v_self->predicted_state_cov.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 5613; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
    __pyx_t_33 = 0;
    __pyx_t_34 = 0;
    __pyx_t_35 = 0;
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dcopy((&__pyx_v_self->k_states2), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=2 */ (( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_self->predicted_state_cov.data) + __pyx_t_30)) ) + __pyx_t_31 * __pyx_v_self->predicted_state_cov.strides[1]) ) + __pyx_t_32 * __pyx_v_self->predicted_state_cov.strides[2]) )))), (&__pyx_v_inc), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=2 */ (( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_self->predicted_state_cov.data) + __pyx_t_33)) ) + __pyx_t_34 * __pyx_v_self->predicted_state_cov.strides[1]) ) + __pyx_t_35 * __pyx_v_self->predicted_state_cov.strides[2]) )))), (&__pyx_v_inc));

    /* "statsmodels\tsa\statespace\_statespace.pyx":5616
 * 
 *             # Predicted: 2 -> 1
 *             dcopy(&self.k_states, &self.predicted_state[0, 2], &inc, &self.predicted_state[0, 1], &inc)             # <<<<<<<<<<<<<<
 *             dcopy(&self.k_states2, &self.predicted_state_cov[0, 0, 2], &inc, &self.predicted_state_cov[0, 0, 1], &inc)
 * 
 */
    if (unlikely(!__pyx_v_self->predicted_state.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 5616; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
    __pyx_t_36 = 0;
    __pyx_t_37 = 2;
    if (unlikely(!__pyx_v_self->predicted_state.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 5616; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
    __pyx_t_38 = 0;
    __pyx_t_39 = 1;
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dcopy((&__pyx_v_self->k_states), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_self->predicted_state.data) + __pyx_t_36)) ) + __pyx_t_37 * __pyx_v_self->predicted_state.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_self->predicted_state.data) + __pyx_t_38)) ) + __pyx_t_39 * __pyx_v_self->predicted_state.strides[1]) )))), (&__pyx_v_inc));

    /* "statsmodels\tsa\statespace\_statespace.pyx":5617
 *             # Predicted: 2 -> 1
 *             dcopy(&self.k_states, &self.predicted_state[0, 2], &inc, &self.predicted_state[0, 1], &inc)
 *             dcopy(&self.k_states2, &self.predicted_state_cov[0, 0, 2], &inc, &self.predicted_state_cov[0, 0, 1], &inc)             # <<<<<<<<<<<<<<
 * 
 * cpdef _dcompute_coefficients_from_multivariate_pacf(np.float64_t [::1,:] partial_autocorrelations,
 */
    if (unlikely(!__pyx_v_self->predicted_state_cov.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 5617; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
    __pyx_t_40 = 0;
    __pyx_t_41 = 0;
    __pyx_t_42 = 2;
    if (unlikely(!__pyx_v_self->predicted_state_cov.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 5617; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
    __pyx_t_43 = 0;
    __pyx_t_44 = 0;
    __pyx_t_45 = 1;
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dcopy((&__pyx_v_self->k_states2), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=2 */ (( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_self->predicted_state_cov.data) + __pyx_t_40)) ) + __pyx_t_41 * __pyx_v_self->predicted_state_cov.strides[1]) ) + __pyx_t_42 * __pyx_v_self->predicted_state_cov.strides[2]) )))), (&__pyx_v_inc), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=2 */ (( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_self->predicted_state_cov.data) + __pyx_t_43)) ) + __pyx_t_44 * __pyx_v_self->predicted_state_cov.strides[1]) ) + __pyx_t_45 * __pyx_v_self->predicted_state_cov.strides[2]) )))), (&__pyx_v_inc));
    goto __pyx_L5;
  }
  __pyx_L5:;

  /* "statsmodels\tsa\statespace\_statespace.pyx":5596
 *                 self.converged_determinant = self.determinant
 * 
 *     cdef void migrate_storage(self):             # <<<<<<<<<<<<<<
 *         cdef int inc = 1
 * 
 */

  /* function exit code */
  goto __pyx_L0;
  __pyx_L1_error:;
  __Pyx_WriteUnraisable("statsmodels.tsa.statespace._statespace.dKalmanFilter.migrate_storage", __pyx_clineno, __pyx_lineno, __pyx_filename, 0);
  __pyx_L0:;
  __Pyx_RefNannyFinishContext();
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/* "statsmodels\tsa\statespace\_statespace.pyx":4905
 * 
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  if (unlikely(!__pyx_t_5.memview)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 5694; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
  __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
  __pyx_v_backwards1 = __pyx_t_5;
  __pyx_t_5.memview = NULL;
  __pyx_t_5.data = NULL;

  /* "statsmodels\tsa\statespace\_statespace.pyx":5695
 *     # \phi_{s,k}^*
 *     backwards1 = np.PyArray_ZEROS(2, dim2, np.NPY_FLOAT64, FORTRAN)
 *     backwards2 = np.PyArray_ZEROS(2, dim2, np.NPY_FLOAT64, FORTRAN)             # <<<<<<<<<<<<<<
 * 
 *     dim2[0] = k_endog; dim2[1] = k_endog_order1;
 */
  __pyx_t_1 = PyArray_ZEROS(2, __pyx_v_dim2, NPY_FLOAT64, __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_FORTRAN); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 5695; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
  __Pyx_GOTREF(__pyx_t_1);
  __pyx_t_5 = __Pyx_PyObject_to_MemoryviewSlice_dcd__nn___pyx_t_5numpy_float64_t(__pyx_t_1);
  if (unlikely(!__pyx_t_5.memview)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 5695; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
  __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
  __pyx_v_backwards2 = __pyx_t_5;
  __pyx_t_5.memview = NULL;
  __pyx_t_5.data = NULL;

  /* "statsmodels\tsa\statespace\_statespace.pyx":5697
 *     backwards2 = np.PyArray_ZEROS(2, dim2, np.NPY_FLOAT64, FORTRAN)
 * 
 *     dim2[0] = k_endog; dim2[1] = k_endog_order1;             # <<<<<<<<<<<<<<
 *     autocovariances = np.PyArray_ZEROS(2, dim2, np.NPY_FLOAT64, FORTRAN)
 * 
 */
  (__pyx_v_dim2[0]) = __pyx_v_k_endog;
  (__pyx_v_dim2[1]) = __pyx_v_k_endog_order1;

  /* "statsmodels\tsa\statespace\_statespace.pyx":5698
 * 
 *     dim2[0] = k_endog; dim2[1] = k_endog_order1;
 *     autocovariances = np.PyArray_ZEROS(2, dim2, np.NPY_FLOAT64, FORTRAN)             # <<<<<<<<<<<<<<
 * 
 *     dcopy(&k_endog2, &error_variance[0,0], &inc, &forward_variance[0,0], &inc)   # \Sigma_s
 */
  __pyx_t_1 = PyArray_ZEROS(2, __pyx_v_dim2, NPY_FLOAT64, __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_FORTRAN); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 5698; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
  __Pyx_GOTREF(__pyx_t_1);
  __pyx_t_5 = __Pyx_PyObject_to_MemoryviewSlice_dcd__nn___pyx_t_5numpy_float64_t(__pyx_t_1);
  if (unlikely(!__pyx_t_5.memview)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 5698; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
  __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
  __pyx_v_autocovariances = __pyx_t_5;
  __pyx_t_5.memview = NULL;
  __pyx_t_5.data = NULL;

  /* "statsmodels\tsa\statespace\_statespace.pyx":5700
 *     autocovariances = np.PyArray_ZEROS(2, dim2, np.NPY_FLOAT64, FORTRAN)
 * 
 *     dcopy(&k_endog2, &error_variance[0,0], &inc, &forward_variance[0,0], &inc)   # \Sigma_s             # <<<<<<<<<<<<<<
 *     dcopy(&k_endog2, &error_variance[0,0], &inc, &backward_variance[0,0], &inc)  # \Sigma_s^*,  s = 0, ..., p
 *     dcopy(&k_endog2, &error_variance[0,0], &inc, &autocovariances[0,0], &inc)  # \Gamma_s
 */
  __pyx_t_9 = 0;
  __pyx_t_10 = 0;
  __pyx_t_11 = 0;
  __pyx_t_12 = 0;
  __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dcopy((&__pyx_v_k_endog2), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_error_variance.data) + __pyx_t_9)) ) + __pyx_t_10 * __pyx_v_error_variance.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_forward_variance.data) + __pyx_t_11)) ) + __pyx_t_12 * __pyx_v_forward_variance.strides[1]) )))), (&__pyx_v_inc));

  /* "statsmodels\tsa\statespace\_statespace.pyx":5701
 * 
 *     dcopy(&k_endog2, &error_variance[0,0], &inc, &forward_variance[0,0], &inc)   # \Sigma_s
 *     dcopy(&k_endog2, &error_variance[0,0], &inc, &backward_variance[0,0], &inc)  # \Sigma_s^*,  s = 0, ..., p             # <<<<<<<<<<<<<<
 *     dcopy(&k_endog2, &error_variance[0,0], &inc, &autocovariances[0,0], &inc)  # \Gamma_s
 * 
 */
  __pyx_t_13 = 0;
  __pyx_t_14 = 0;
  __pyx_t_15 = 0;
  __pyx_t_16 = 0;
  __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dcopy((&__pyx_v_k_endog2), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_error_variance.data) + __pyx_t_13)) ) + __pyx_t_14 * __pyx_v_error_variance.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_backward_variance.data) + __pyx_t_15)) ) + __pyx_t_16 * __pyx_v_backward_variance.strides[1]) )))), (&__pyx_v_inc));

  /* "statsmodels\tsa\statespace\_statespace.pyx":5702
 *     dcopy(&k_endog2, &error_variance[0,0], &inc, &forward_variance[0,0], &inc)   # \Sigma_s
 *     dcopy(&k_endog2, &error_variance[0,0], &inc, &backward_variance[0,0], &inc)  # \Sigma_s^*,  s = 0, ..., p
 *     dcopy(&k_endog2, &error_variance[0,0], &inc, &autocovariances[0,0], &inc)  # \Gamma_s             # <<<<<<<<<<<<<<
 * 
 *     # error_variance_factor = linalg.cholesky(error_variance, lower=True)
 */
  __pyx_t_17 = 0;
  __pyx_t_18 = 0;
  __pyx_t_19 = 0;
  __pyx_t_20 = 0;
  __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dcopy((&__pyx_v_k_endog2), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_error_variance.data) + __pyx_t_17)) ) + __pyx_t_18 * __pyx_v_error_variance.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_autocovariances.data) + __pyx_t_19)) ) + __pyx_t_20 * __pyx_v_autocovariances.strides[1]) )))), (&__pyx_v_inc));

  /* "statsmodels\tsa\statespace\_statespace.pyx":5705
 * 
 *     # error_variance_factor = linalg.cholesky(error_variance, lower=True)
 *     dcopy(&k_endog2, &error_variance[0,0], &inc, &forward_factors[0,0], &inc)             # <<<<<<<<<<<<<<
 *     dpotrf("L", &k_endog, &forward_factors[0,0], &k_endog, &info)
 *     dcopy(&k_endog2, &forward_factors[0,0], &inc, &backward_factors[0,0], &inc)
 */
  __pyx_t_21 = 0;
  __pyx_t_22 = 0;
  __pyx_t_23 = 0;
  __pyx_t_24 = 0;
  __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dcopy((&__pyx_v_k_endog2), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_error_variance.data) + __pyx_t_21)) ) + __pyx_t_22 * __pyx_v_error_variance.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_forward_factors.data) + __pyx_t_23)) ) + __pyx_t_24 * __pyx_v_forward_factors.strides[1]) )))), (&__pyx_v_inc));

  /* "statsmodels\tsa\statespace\_statespace.pyx":5706
 *     # error_variance_factor = linalg.cholesky(error_variance, lower=True)
 *     dcopy(&k_endog2, &error_variance[0,0], &inc, &forward_factors[0,0], &inc)
 *     dpotrf("L", &k_endog, &forward_factors[0,0], &k_endog, &info)             # <<<<<<<<<<<<<<
 *     dcopy(&k_endog2, &forward_factors[0,0], &inc, &backward_factors[0,0], &inc)
 * 
 */
  __pyx_t_25 = 0;
  __pyx_t_26 = 0;
  __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dpotrf(__pyx_k_L, (&__pyx_v_k_endog), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_forward_factors.data) + __pyx_t_25)) ) + __pyx_t_26 * __pyx_v_forward_factors.strides[1]) )))), (&__pyx_v_k_endog), (&__pyx_v_info));

  /* "statsmodels\tsa\statespace\_statespace.pyx":5707
 *     dcopy(&k_endog2, &error_variance[0,0], &inc, &forward_factors[0,0], &inc)
 *     dpotrf("L", &k_endog, &forward_factors[0,0], &k_endog, &info)
 *     dcopy(&k_endog2, &forward_factors[0,0], &inc, &backward_factors[0,0], &inc)             # <<<<<<<<<<<<<<
 * 
 *     # We fill in the entries as follows:
 */
  __pyx_t_27 = 0;
  __pyx_t_28 = 0;
  __pyx_t_29 = 0;
  __pyx_t_30 = 0;
  __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dcopy((&__pyx_v_k_endog2), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_forward_factors.data) + __pyx_t_27)) ) + __pyx_t_28 * __pyx_v_forward_factors.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_backward_factors.data) + __pyx_t_29)) ) + __pyx_t_30 * __pyx_v_backward_factors.strides[1]) )))), (&__pyx_v_inc));

  /* "statsmodels\tsa\statespace\_statespace.pyx":5716
 *     # [p,p], [p,1], ..., [p,p-1]
 *     # the last row, correctly ordered, is then used as the coefficients
 *     for s in range(order):  # s = 0, ..., p-1             # <<<<<<<<<<<<<<
 *         if s % 2 == 0:
 *             forwards = &forwards1[0, 0]
 */
  __pyx_t_31 = __pyx_v_order;
  for (__pyx_t_32 = 0; __pyx_t_32 < __pyx_t_31; __pyx_t_32+=1) {
    __pyx_v_s = __pyx_t_32;

    /* "statsmodels\tsa\statespace\_statespace.pyx":5717
 *     # the last row, correctly ordered, is then used as the coefficients
 *     for s in range(order):  # s = 0, ..., p-1
 *         if s % 2 == 0:             # <<<<<<<<<<<<<<
 *             forwards = &forwards1[0, 0]
 *             prev_forwards = &forwards2[0, 0]
 */
    __pyx_t_3 = ((__Pyx_mod_long(__pyx_v_s, 2) == 0) != 0);
    if (__pyx_t_3) {

      /* "statsmodels\tsa\statespace\_statespace.pyx":5718
 *     for s in range(order):  # s = 0, ..., p-1
 *         if s % 2 == 0:
 *             forwards = &forwards1[0, 0]             # <<<<<<<<<<<<<<
 *             prev_forwards = &forwards2[0, 0]
 *             backwards = &backwards1[0, 0]
 */
      __pyx_t_33 = 0;
      __pyx_t_34 = 0;
      __pyx_v_forwards = (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_forwards1.data) + __pyx_t_33)) ) + __pyx_t_34 * __pyx_v_forwards1.strides[1]) ))));

      /* "statsmodels\tsa\statespace\_statespace.pyx":5719
 *         if s % 2 == 0:
 *             forwards = &forwards1[0, 0]
 *             prev_forwards = &forwards2[0, 0]             # <<<<<<<<<<<<<<
 *             backwards = &backwards1[0, 0]
 *             prev_backwards = &backwards2[0, 0]
 */
      __pyx_t_35 = 0;
      __pyx_t_36 = 0;
      __pyx_v_prev_forwards = (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_forwards2.data) + __pyx_t_35)) ) + __pyx_t_36 * __pyx_v_forwards2.strides[1]) ))));

      /* "statsmodels\tsa\statespace\_statespace.pyx":5720
 *             forwards = &forwards1[0, 0]
 *             prev_forwards = &forwards2[0, 0]
 *             backwards = &backwards1[0, 0]             # <<<<<<<<<<<<<<
 *             prev_backwards = &backwards2[0, 0]
 *         else:
 */
      __pyx_t_37 = 0;
      __pyx_t_38 = 0;
      __pyx_v_backwards = (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_backwards1.data) + __pyx_t_37)) ) + __pyx_t_38 * __pyx_v_backwards1.strides[1]) ))));

      /* "statsmodels\tsa\statespace\_statespace.pyx":5721
 *             prev_forwards = &forwards2[0, 0]
 *             backwards = &backwards1[0, 0]
 *             prev_backwards = &backwards2[0, 0]             # <<<<<<<<<<<<<<
 *         else:
 *             forwards = &forwards2[0, 0]
 */
      __pyx_t_39 = 0;
      __pyx_t_40 = 0;
      __pyx_v_prev_backwards = (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_backwards2.data) + __pyx_t_39)) ) + __pyx_t_40 * __pyx_v_backwards2.strides[1]) ))));
      goto __pyx_L6;
    }
    /*else*/ {

      /* "statsmodels\tsa\statespace\_statespace.pyx":5723
 *             prev_backwards = &backwards2[0, 0]
 *         else:
 *             forwards = &forwards2[0, 0]             # <<<<<<<<<<<<<<
 *             prev_forwards = &forwards1[0, 0]
 *             backwards = &backwards2[0, 0]
 */
      __pyx_t_41 = 0;
      __pyx_t_42 = 0;
      __pyx_v_forwards = (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_forwards2.data) + __pyx_t_41)) ) + __pyx_t_42 * __pyx_v_forwards2.strides[1]) ))));

      /* "statsmodels\tsa\statespace\_statespace.pyx":5724
 *         else:
 *             forwards = &forwards2[0, 0]
 *             prev_forwards = &forwards1[0, 0]             # <<<<<<<<<<<<<<
 *             backwards = &backwards2[0, 0]
 *             prev_backwards = &backwards1[0, 0]
 */
      __pyx_t_43 = 0;
      __pyx_t_44 = 0;
      __pyx_v_prev_forwards = (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_forwards1.data) + __pyx_t_43)) ) + __pyx_t_44 * __pyx_v_forwards1.strides[1]) ))));

      /* "statsmodels\tsa\statespace\_statespace.pyx":5725
 *             forwards = &forwards2[0, 0]
 *             prev_forwards = &forwards1[0, 0]
 *             backwards = &backwards2[0, 0]             # <<<<<<<<<<<<<<
 *             prev_backwards = &backwards1[0, 0]
 * 
 */
      __pyx_t_45 = 0;
      __pyx_t_46 = 0;
      __pyx_v_backwards = (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_backwards2.data) + __pyx_t_45)) ) + __pyx_t_46 * __pyx_v_backwards2.strides[1]) ))));

      /* "statsmodels\tsa\statespace\_statespace.pyx":5726
 *             prev_forwards = &forwards1[0, 0]
 *             backwards = &backwards2[0, 0]
 *             prev_backwards = &backwards1[0, 0]             # <<<<<<<<<<<<<<
 * 
 *         # Create the "last" (k = s+1) matrix
 */
      __pyx_t_47 = 0;
      __pyx_t_48 = 0;
      __pyx_v_prev_backwards = (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_backwards1.data) + __pyx_t_47)) ) + __pyx_t_48 * __pyx_v_backwards1.strides[1]) ))));
    }
    __pyx_L6:;

    /* "statsmodels\tsa\statespace\_statespace.pyx":5740
 *         #         lower=True, trans='T').T
 *         # )
 *         for k in range(k_endog):             # <<<<<<<<<<<<<<
 *             dcopy(&k_endog, &partial_autocorrelations[k,s*k_endog], &k_endog, &tmp[0, k], &inc)
 *         dtrtrs("L", "T", "N", &k_endog, &k_endog, &backward_factors[0,0], &k_endog,
 */
    __pyx_t_49 = __pyx_v_k_endog;
    for (__pyx_t_50 = 0; __pyx_t_50 < __pyx_t_49; __pyx_t_50+=1) {
      __pyx_v_k = __pyx_t_50;

      /* "statsmodels\tsa\statespace\_statespace.pyx":5741
 *         # )
 *         for k in range(k_endog):
 *             dcopy(&k_endog, &partial_autocorrelations[k,s*k_endog], &k_endog, &tmp[0, k], &inc)             # <<<<<<<<<<<<<<
 *         dtrtrs("L", "T", "N", &k_endog, &k_endog, &backward_factors[0,0], &k_endog,
 *                                                            &tmp[0, 0], &k_endog, &info)
 */
      __pyx_t_51 = __pyx_v_k;
      __pyx_t_52 = (__pyx_v_s * __pyx_v_k_endog);
      __pyx_t_53 = 0;
      __pyx_t_54 = __pyx_v_k;
      __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dcopy((&__pyx_v_k_endog), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_partial_autocorrelations.data) + __pyx_t_51)) ) + __pyx_t_52 * __pyx_v_partial_autocorrelations.strides[1]) )))), (&__pyx_v_k_endog), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_tmp.data) + __pyx_t_53)) ) + __pyx_t_54 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_inc));
    }

    /* "statsmodels\tsa\statespace\_statespace.pyx":5742
 *         for k in range(k_endog):
 *             dcopy(&k_endog, &partial_autocorrelations[k,s*k_endog], &k_endog, &tmp[0, k], &inc)
 *         dtrtrs("L", "T", "N", &k_endog, &k_endog, &backward_factors[0,0], &k_endog,             # <<<<<<<<<<<<<<
 *                                                            &tmp[0, 0], &k_endog, &info)
 *         # dgemm("N", "T", &k_endog, &k_endog, &k_endog,
 */
    __pyx_t_55 = 0;
    __pyx_t_56 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":5743
 *             dcopy(&k_endog, &partial_autocorrelations[k,s*k_endog], &k_endog, &tmp[0, k], &inc)
 *         dtrtrs("L", "T", "N", &k_endog, &k_endog, &backward_factors[0,0], &k_endog,
 *                                                            &tmp[0, 0], &k_endog, &info)             # <<<<<<<<<<<<<<
 *         # dgemm("N", "T", &k_endog, &k_endog, &k_endog,
 *         #   &alpha, &forward_factors[0,0], &k_endog,
 */
    __pyx_t_57 = 0;
    __pyx_t_58 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":5742
 *         for k in range(k_endog):
 *             dcopy(&k_endog, &partial_autocorrelations[k,s*k_endog], &k_endog, &tmp[0, k], &inc)
 *         dtrtrs("L", "T", "N", &k_endog, &k_endog, &backward_factors[0,0], &k_endog,             # <<<<<<<<<<<<<<
 *                                                            &tmp[0, 0], &k_endog, &info)
 *         # dgemm("N", "T", &k_endog, &k_endog, &k_endog,
 */
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dtrtrs(__pyx_k_L, __pyx_k_T, __pyx_k_N, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_backward_factors.data) + __pyx_t_55)) ) + __pyx_t_56 * __pyx_v_backward_factors.strides[1]) )))), (&__pyx_v_k_endog), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_tmp.data) + __pyx_t_57)) ) + __pyx_t_58 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_k_endog), (&__pyx_v_info));

    /* "statsmodels\tsa\statespace\_statespace.pyx":5749
 *         #   &beta, &forwards[s*k_endog2], &k_endog)
 *         dtrmm("R", "L", "T", "N", &k_endog, &k_endog,
 *           &alpha, &forward_factors[0,0], &k_endog,             # <<<<<<<<<<<<<<
 *                   &tmp[0, 0], &k_endog)
 *         for k in range(k_endog):
 */
    __pyx_t_59 = 0;
    __pyx_t_60 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":5750
 *         dtrmm("R", "L", "T", "N", &k_endog, &k_endog,
 *           &alpha, &forward_factors[0,0], &k_endog,
 *                   &tmp[0, 0], &k_endog)             # <<<<<<<<<<<<<<
 *         for k in range(k_endog):
 *             dcopy(&k_endog, &tmp[k,0], &k_endog, &forwards[s*k_endog2 + k*k_endog], &inc)
 */
    __pyx_t_61 = 0;
    __pyx_t_62 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":5748
 *         #           &tmp[0, 0], &k_endog,
 *         #   &beta, &forwards[s*k_endog2], &k_endog)
 *         dtrmm("R", "L", "T", "N", &k_endog, &k_endog,             # <<<<<<<<<<<<<<
 *           &alpha, &forward_factors[0,0], &k_endog,
 *                   &tmp[0, 0], &k_endog)
 */
    __pyx_v_dtrmm(__pyx_k_R, __pyx_k_L, __pyx_k_T, __pyx_k_N, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_alpha), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_forward_factors.data) + __pyx_t_59)) ) + __pyx_t_60 * __pyx_v_forward_factors.strides[1]) )))), (&__pyx_v_k_endog), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_tmp.data) + __pyx_t_61)) ) + __pyx_t_62 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_k_endog));

    /* "statsmodels\tsa\statespace\_statespace.pyx":5751
 *           &alpha, &forward_factors[0,0], &k_endog,
 *                   &tmp[0, 0], &k_endog)
 *         for k in range(k_endog):             # <<<<<<<<<<<<<<
 *             dcopy(&k_endog, &tmp[k,0], &k_endog, &forwards[s*k_endog2 + k*k_endog], &inc)
 * 
 */
    __pyx_t_49 = __pyx_v_k_endog;
    for (__pyx_t_50 = 0; __pyx_t_50 < __pyx_t_49; __pyx_t_50+=1) {
      __pyx_v_k = __pyx_t_50;

      /* "statsmodels\tsa\statespace\_statespace.pyx":5752
 *                   &tmp[0, 0], &k_endog)
 *         for k in range(k_endog):
 *             dcopy(&k_endog, &tmp[k,0], &k_endog, &forwards[s*k_endog2 + k*k_endog], &inc)             # <<<<<<<<<<<<<<
 * 
 *         # P' L^{-1} = x
 */
      __pyx_t_63 = __pyx_v_k;
      __pyx_t_64 = 0;
      __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dcopy((&__pyx_v_k_endog), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_tmp.data) + __pyx_t_63)) ) + __pyx_t_64 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_k_endog), (&(__pyx_v_forwards[((__pyx_v_s * __pyx_v_k_endog2) + (__pyx_v_k * __pyx_v_k_endog))])), (&__pyx_v_inc));
    }

    /* "statsmodels\tsa\statespace\_statespace.pyx":5763
 *         #         lower=True, trans='T').T
 *         # )
 *         dcopy(&k_endog2, &partial_autocorrelations[0, s*k_endog], &inc, &tmp[0, 0], &inc)             # <<<<<<<<<<<<<<
 *         dtrtrs("L", "T", "N", &k_endog, &k_endog, &forward_factors[0, 0], &k_endog,
 *                                                            &tmp[0, 0], &k_endog, &info)
 */
    __pyx_t_65 = 0;
    __pyx_t_49 = (__pyx_v_s * __pyx_v_k_endog);
    __pyx_t_66 = 0;
    __pyx_t_67 = 0;
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dcopy((&__pyx_v_k_endog2), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_partial_autocorrelations.data) + __pyx_t_65)) ) + __pyx_t_49 * __pyx_v_partial_autocorrelations.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_tmp.data) + __pyx_t_66)) ) + __pyx_t_67 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_inc));

    /* "statsmodels\tsa\statespace\_statespace.pyx":5764
 *         # )
 *         dcopy(&k_endog2, &partial_autocorrelations[0, s*k_endog], &inc, &tmp[0, 0], &inc)
 *         dtrtrs("L", "T", "N", &k_endog, &k_endog, &forward_factors[0, 0], &k_endog,             # <<<<<<<<<<<<<<
 *                                                            &tmp[0, 0], &k_endog, &info)
 *         # dgemm("N", "T", &k_endog, &k_endog, &k_endog,
 */
    __pyx_t_68 = 0;
    __pyx_t_69 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":5765
 *         dcopy(&k_endog2, &partial_autocorrelations[0, s*k_endog], &inc, &tmp[0, 0], &inc)
 *         dtrtrs("L", "T", "N", &k_endog, &k_endog, &forward_factors[0, 0], &k_endog,
 *                                                            &tmp[0, 0], &k_endog, &info)             # <<<<<<<<<<<<<<
 *         # dgemm("N", "T", &k_endog, &k_endog, &k_endog,
 *         #   &alpha, &backward_factors[0, 0], &k_endog,
 */
    __pyx_t_70 = 0;
    __pyx_t_71 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":5764
 *         # )
 *         dcopy(&k_endog2, &partial_autocorrelations[0, s*k_endog], &inc, &tmp[0, 0], &inc)
 *         dtrtrs("L", "T", "N", &k_endog, &k_endog, &forward_factors[0, 0], &k_endog,             # <<<<<<<<<<<<<<
 *                                                            &tmp[0, 0], &k_endog, &info)
 *         # dgemm("N", "T", &k_endog, &k_endog, &k_endog,
 */
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dtrtrs(__pyx_k_L, __pyx_k_T, __pyx_k_N, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_forward_factors.data) + __pyx_t_68)) ) + __pyx_t_69 * __pyx_v_forward_factors.strides[1]) )))), (&__pyx_v_k_endog), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_tmp.data) + __pyx_t_70)) ) + __pyx_t_71 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_k_endog), (&__pyx_v_info));

    /* "statsmodels\tsa\statespace\_statespace.pyx":5771
 *         #   &beta, &backwards[s * k_endog2], &k_endog)
 *         dtrmm("R", "L", "T", "N", &k_endog, &k_endog,
 *           &alpha, &backward_factors[0,0], &k_endog,             # <<<<<<<<<<<<<<
 *                   &tmp[0, 0], &k_endog)
 *         for k in range(k_endog):
 */
    __pyx_t_72 = 0;
    __pyx_t_73 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":5772
 *         dtrmm("R", "L", "T", "N", &k_endog, &k_endog,
 *           &alpha, &backward_factors[0,0], &k_endog,
 *                   &tmp[0, 0], &k_endog)             # <<<<<<<<<<<<<<
 *         for k in range(k_endog):
 *             dcopy(&k_endog, &tmp[k,0], &k_endog, &backwards[s*k_endog2 + k*k_endog], &inc)
 */
    __pyx_t_74 = 0;
    __pyx_t_75 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":5770
 *         #           &tmp[0, 0], &k_endog,
 *         #   &beta, &backwards[s * k_endog2], &k_endog)
 *         dtrmm("R", "L", "T", "N", &k_endog, &k_endog,             # <<<<<<<<<<<<<<
 *           &alpha, &backward_factors[0,0], &k_endog,
 *                   &tmp[0, 0], &k_endog)
 */
    __pyx_v_dtrmm(__pyx_k_R, __pyx_k_L, __pyx_k_T, __pyx_k_N, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_alpha), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_backward_factors.data) + __pyx_t_72)) ) + __pyx_t_73 * __pyx_v_backward_factors.strides[1]) )))), (&__pyx_v_k_endog), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_tmp.data) + __pyx_t_74)) ) + __pyx_t_75 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_k_endog));

    /* "statsmodels\tsa\statespace\_statespace.pyx":5773
 *           &alpha, &backward_factors[0,0], &k_endog,
 *                   &tmp[0, 0], &k_endog)
 *         for k in range(k_endog):             # <<<<<<<<<<<<<<
 *             dcopy(&k_endog, &tmp[k,0], &k_endog, &backwards[s*k_endog2 + k*k_endog], &inc)
 * 
 */
    __pyx_t_50 = __pyx_v_k_endog;
    for (__pyx_t_76 = 0; __pyx_t_76 < __pyx_t_50; __pyx_t_76+=1) {
      __pyx_v_k = __pyx_t_76;

      /* "statsmodels\tsa\statespace\_statespace.pyx":5774
 *                   &tmp[0, 0], &k_endog)
 *         for k in range(k_endog):
 *             dcopy(&k_endog, &tmp[k,0], &k_endog, &backwards[s*k_endog2 + k*k_endog], &inc)             # <<<<<<<<<<<<<<
 * 
 *         # Update the variance
 */
      __pyx_t_77 = __pyx_v_k;
      __pyx_t_78 = 0;
      __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dcopy((&__pyx_v_k_endog), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_tmp.data) + __pyx_t_77)) ) + __pyx_t_78 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_k_endog), (&(__pyx_v_backwards[((__pyx_v_s * __pyx_v_k_endog2) + (__pyx_v_k * __pyx_v_k_endog))])), (&__pyx_v_inc));
    }

    /* "statsmodels\tsa\statespace\_statespace.pyx":5783
 *         # tmpT = np.dot(backward_variance.T, forwards[:, s*k_endog:(s+1)*k_endog].T)
 *         dgemm("T", "T", &k_endog, &k_endog, &k_endog,
 *           &alpha, &backward_variance[0, 0], &k_endog,             # <<<<<<<<<<<<<<
 *                   &forwards[s * k_endog2], &k_endog,
 *           &beta, &tmp[0, 0], &k_endog)
 */
    __pyx_t_79 = 0;
    __pyx_t_80 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":5785
 *           &alpha, &backward_variance[0, 0], &k_endog,
 *                   &forwards[s * k_endog2], &k_endog,
 *           &beta, &tmp[0, 0], &k_endog)             # <<<<<<<<<<<<<<
 *         # autocovariances[:, (s+1)*k_endog:(s+2)*k_endog] = tmp.copy().T
 *         dcopy(&k_endog2, &tmp[0, 0], &inc, &autocovariances[0, (s+1)*k_endog], &inc)
 */
    __pyx_t_81 = 0;
    __pyx_t_82 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":5782
 *         # tmp = np.dot(forwards[:, s*k_endog:(s+1)*k_endog], backward_variance)
 *         # tmpT = np.dot(backward_variance.T, forwards[:, s*k_endog:(s+1)*k_endog].T)
 *         dgemm("T", "T", &k_endog, &k_endog, &k_endog,             # <<<<<<<<<<<<<<
 *           &alpha, &backward_variance[0, 0], &k_endog,
 *                   &forwards[s * k_endog2], &k_endog,
 */
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dgemm(__pyx_k_T, __pyx_k_T, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_alpha), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_backward_variance.data) + __pyx_t_79)) ) + __pyx_t_80 * __pyx_v_backward_variance.strides[1]) )))), (&__pyx_v_k_endog), (&(__pyx_v_forwards[(__pyx_v_s * __pyx_v_k_endog2)])), (&__pyx_v_k_endog), (&__pyx_v_beta), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_tmp.data) + __pyx_t_81)) ) + __pyx_t_82 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_k_endog));

    /* "statsmodels\tsa\statespace\_statespace.pyx":5787
 *           &beta, &tmp[0, 0], &k_endog)
 *         # autocovariances[:, (s+1)*k_endog:(s+2)*k_endog] = tmp.copy().T
 *         dcopy(&k_endog2, &tmp[0, 0], &inc, &autocovariances[0, (s+1)*k_endog], &inc)             # <<<<<<<<<<<<<<
 * 
 *         # Create the remaining k = 1, ..., s matrices,
 */
    __pyx_t_83 = 0;
    __pyx_t_84 = 0;
    __pyx_t_85 = 0;
    __pyx_t_86 = ((__pyx_v_s + 1) * __pyx_v_k_endog);
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dcopy((&__pyx_v_k_endog2), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_tmp.data) + __pyx_t_83)) ) + __pyx_t_84 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_autocovariances.data) + __pyx_t_85)) ) + __pyx_t_86 * __pyx_v_autocovariances.strides[1]) )))), (&__pyx_v_inc));

    /* "statsmodels\tsa\statespace\_statespace.pyx":5791
 *         # Create the remaining k = 1, ..., s matrices,
 *         # only has an effect if s >= 1
 *         for k in range(s):             # <<<<<<<<<<<<<<
 *             # forwards[:, k*k_endog:(k+1)*k_endog] = (
 *             #     prev_forwards[:, k*k_endog:(k+1)*k_endog] -
 */
    __pyx_t_50 = __pyx_v_s;
    for (__pyx_t_76 = 0; __pyx_t_76 < __pyx_t_50; __pyx_t_76+=1) {
      __pyx_v_k = __pyx_t_76;

      /* "statsmodels\tsa\statespace\_statespace.pyx":5799
 *             #     )
 *             # )
 *             dcopy(&k_endog2, &prev_forwards[k * k_endog2], &inc, &forwards[k * k_endog2], &inc)             # <<<<<<<<<<<<<<
 *             dgemm("N", "N", &k_endog, &k_endog, &k_endog,
 *               &gamma, &forwards[s * k_endog2], &k_endog,
 */
      __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dcopy((&__pyx_v_k_endog2), (&(__pyx_v_prev_forwards[(__pyx_v_k * __pyx_v_k_endog2)])), (&__pyx_v_inc), (&(__pyx_v_forwards[(__pyx_v_k * __pyx_v_k_endog2)])), (&__pyx_v_inc));

      /* "statsmodels\tsa\statespace\_statespace.pyx":5800
 *             # )
 *             dcopy(&k_endog2, &prev_forwards[k * k_endog2], &inc, &forwards[k * k_endog2], &inc)
 *             dgemm("N", "N", &k_endog, &k_endog, &k_endog,             # <<<<<<<<<<<<<<
 *               &gamma, &forwards[s * k_endog2], &k_endog,
 *                       &prev_backwards[(s - k - 1) * k_endog2], &k_endog,
 */
      __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dgemm(__pyx_k_N, __pyx_k_N, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_gamma), (&(__pyx_v_forwards[(__pyx_v_s * __pyx_v_k_endog2)])), (&__pyx_v_k_endog), (&(__pyx_v_prev_backwards[(((__pyx_v_s - __pyx_v_k) - 1) * __pyx_v_k_endog2)])), (&__pyx_v_k_endog), (&__pyx_v_alpha), (&(__pyx_v_forwards[(__pyx_v_k * __pyx_v_k_endog2)])), (&__pyx_v_k_endog));

      /* "statsmodels\tsa\statespace\_statespace.pyx":5812
 *             #     )
 *             # )
 *             dcopy(&k_endog2, &prev_backwards[k * k_endog2], &inc, &backwards[k * k_endog2], &inc)             # <<<<<<<<<<<<<<
 *             dgemm("N", "N", &k_endog, &k_endog, &k_endog,
 *               &gamma, &backwards[s * k_endog2], &k_endog,
 */
      __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dcopy((&__pyx_v_k_endog2), (&(__pyx_v_prev_backwards[(__pyx_v_k * __pyx_v_k_endog2)])), (&__pyx_v_inc), (&(__pyx_v_backwards[(__pyx_v_k * __pyx_v_k_endog2)])), (&__pyx_v_inc));

      /* "statsmodels\tsa\statespace\_statespace.pyx":5813
 *             # )
 *             dcopy(&k_endog2, &prev_backwards[k * k_endog2], &inc, &backwards[k * k_endog2], &inc)
 *             dgemm("N", "N", &k_endog, &k_endog, &k_endog,             # <<<<<<<<<<<<<<
 *               &gamma, &backwards[s * k_endog2], &k_endog,
 *                       &prev_forwards[(s - k - 1) * k_endog2], &k_endog,
 */
      __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dgemm(__pyx_k_N, __pyx_k_N, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_gamma), (&(__pyx_v_backwards[(__pyx_v_s * __pyx_v_k_endog2)])), (&__pyx_v_k_endog), (&(__pyx_v_prev_forwards[(((__pyx_v_s - __pyx_v_k) - 1) * __pyx_v_k_endog2)])), (&__pyx_v_k_endog), (&__pyx_v_alpha), (&(__pyx_v_backwards[(__pyx_v_k * __pyx_v_k_endog2)])), (&__pyx_v_k_endog));

      /* "statsmodels\tsa\statespace\_statespace.pyx":5823
 *             # )
 *             dgemm("N", "T", &k_endog, &k_endog, &k_endog,
 *               &alpha, &autocovariances[0, (k+1)*k_endog], &k_endog,             # <<<<<<<<<<<<<<
 *                       &prev_forwards[(s - k - 1) * k_endog2], &k_endog,
 *               &alpha, &autocovariances[0, (s+1)*k_endog], &k_endog)
 */
      __pyx_t_87 = 0;
      __pyx_t_88 = ((__pyx_v_k + 1) * __pyx_v_k_endog);

      /* "statsmodels\tsa\statespace\_statespace.pyx":5825
 *               &alpha, &autocovariances[0, (k+1)*k_endog], &k_endog,
 *                       &prev_forwards[(s - k - 1) * k_endog2], &k_endog,
 *               &alpha, &autocovariances[0, (s+1)*k_endog], &k_endog)             # <<<<<<<<<<<<<<
 * 
 *         # Create forward and backwards variances
 */
      __pyx_t_89 = 0;
      __pyx_t_90 = ((__pyx_v_s + 1) * __pyx_v_k_endog);

      /* "statsmodels\tsa\statespace\_statespace.pyx":5822
 *             #     prev_forwards[:, (s-k-1)*k_endog:(s-k)*k_endog].T
 *             # )
 *             dgemm("N", "T", &k_endog, &k_endog, &k_endog,             # <<<<<<<<<<<<<<
 *               &alpha, &autocovariances[0, (k+1)*k_endog], &k_endog,
 *                       &prev_forwards[(s - k - 1) * k_endog2], &k_endog,
 */
      __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dgemm(__pyx_k_N, __pyx_k_T, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_alpha), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_autocovariances.data) + __pyx_t_87)) ) + __pyx_t_88 * __pyx_v_autocovariances.strides[1]) )))), (&__pyx_v_k_endog), (&(__pyx_v_prev_forwards[(((__pyx_v_s - __pyx_v_k) - 1) * __pyx_v_k_endog2)])), (&__pyx_v_k_endog), (&__pyx_v_alpha), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_autocovariances.data) + __pyx_t_89)) ) + __pyx_t_90 * __pyx_v_autocovariances.strides[1]) )))), (&__pyx_v_k_endog));
    }

    /* "statsmodels\tsa\statespace\_statespace.pyx":5837
 *         dgemm("N", "N", &k_endog, &k_endog, &k_endog,
 *           &alpha, &backwards[s * k_endog2], &k_endog,
 *                   &forward_variance[0, 0], &k_endog,             # <<<<<<<<<<<<<<
 *           &beta, &tmp2[0, 0], &k_endog)
 *         dgemm("N", "T", &k_endog, &k_endog, &k_endog,
 */
    __pyx_t_91 = 0;
    __pyx_t_92 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":5838
 *           &alpha, &backwards[s * k_endog2], &k_endog,
 *                   &forward_variance[0, 0], &k_endog,
 *           &beta, &tmp2[0, 0], &k_endog)             # <<<<<<<<<<<<<<
 *         dgemm("N", "T", &k_endog, &k_endog, &k_endog,
 *           &gamma, &tmp2[0, 0], &k_endog,
 */
    __pyx_t_93 = 0;
    __pyx_t_94 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":5835
 *         #     )
 *         # )
 *         dgemm("N", "N", &k_endog, &k_endog, &k_endog,             # <<<<<<<<<<<<<<
 *           &alpha, &backwards[s * k_endog2], &k_endog,
 *                   &forward_variance[0, 0], &k_endog,
 */
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dgemm(__pyx_k_N, __pyx_k_N, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_alpha), (&(__pyx_v_backwards[(__pyx_v_s * __pyx_v_k_endog2)])), (&__pyx_v_k_endog), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_forward_variance.data) + __pyx_t_91)) ) + __pyx_t_92 * __pyx_v_forward_variance.strides[1]) )))), (&__pyx_v_k_endog), (&__pyx_v_beta), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_tmp2.data) + __pyx_t_93)) ) + __pyx_t_94 * __pyx_v_tmp2.strides[1]) )))), (&__pyx_v_k_endog));

    /* "statsmodels\tsa\statespace\_statespace.pyx":5840
 *           &beta, &tmp2[0, 0], &k_endog)
 *         dgemm("N", "T", &k_endog, &k_endog, &k_endog,
 *           &gamma, &tmp2[0, 0], &k_endog,             # <<<<<<<<<<<<<<
 *                   &backwards[s * k_endog2], &k_endog,
 *           &alpha, &backward_variance[0, 0], &k_endog)
 */
    __pyx_t_95 = 0;
    __pyx_t_96 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":5842
 *           &gamma, &tmp2[0, 0], &k_endog,
 *                   &backwards[s * k_endog2], &k_endog,
 *           &alpha, &backward_variance[0, 0], &k_endog)             # <<<<<<<<<<<<<<
 *         # forward_variance = (
 *         #     forward_variance -
 */
    __pyx_t_97 = 0;
    __pyx_t_98 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":5839
 *                   &forward_variance[0, 0], &k_endog,
 *           &beta, &tmp2[0, 0], &k_endog)
 *         dgemm("N", "T", &k_endog, &k_endog, &k_endog,             # <<<<<<<<<<<<<<
 *           &gamma, &tmp2[0, 0], &k_endog,
 *                   &backwards[s * k_endog2], &k_endog,
 */
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dgemm(__pyx_k_N, __pyx_k_T, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_gamma), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_tmp2.data) + __pyx_t_95)) ) + __pyx_t_96 * __pyx_v_tmp2.strides[1]) )))), (&__pyx_v_k_endog), (&(__pyx_v_backwards[(__pyx_v_s * __pyx_v_k_endog2)])), (&__pyx_v_k_endog), (&__pyx_v_alpha), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_backward_variance.data) + __pyx_t_97)) ) + __pyx_t_98 * __pyx_v_backward_variance.strides[1]) )))), (&__pyx_v_k_endog));

    /* "statsmodels\tsa\statespace\_statespace.pyx":5852
 *         # )
 *         dgemm("T", "T", &k_endog, &k_endog, &k_endog,
 *           &gamma, &tmp[0, 0], &k_endog,             # <<<<<<<<<<<<<<
 *                   &forwards[s * k_endog2], &k_endog,
 *           &alpha, &forward_variance[0, 0], &k_endog)
 */
    __pyx_t_99 = 0;
    __pyx_t_100 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":5854
 *           &gamma, &tmp[0, 0], &k_endog,
 *                   &forwards[s * k_endog2], &k_endog,
 *           &alpha, &forward_variance[0, 0], &k_endog)             # <<<<<<<<<<<<<<
 * 
 *         # Cholesky factors
 */
    __pyx_t_101 = 0;
    __pyx_t_102 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":5851
 *         #     np.dot(tmpT.T, forwards[:, s*k_endog:(s+1)*k_endog].T)
 *         # )
 *         dgemm("T", "T", &k_endog, &k_endog, &k_endog,             # <<<<<<<<<<<<<<
 *           &gamma, &tmp[0, 0], &k_endog,
 *                   &forwards[s * k_endog2], &k_endog,
 */
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dgemm(__pyx_k_T, __pyx_k_T, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_gamma), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_tmp.data) + __pyx_t_99)) ) + __pyx_t_100 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_k_endog), (&(__pyx_v_forwards[(__pyx_v_s * __pyx_v_k_endog2)])), (&__pyx_v_k_endog), (&__pyx_v_alpha), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_forward_variance.data) + __pyx_t_101)) ) + __pyx_t_102 * __pyx_v_forward_variance.strides[1]) )))), (&__pyx_v_k_endog));

    /* "statsmodels\tsa\statespace\_statespace.pyx":5859
 *         # forward_factors = linalg.cholesky(forward_variance, lower=True)
 *         # backward_factors =  linalg.cholesky(backward_variance, lower=True)
 *         dcopy(&k_endog2, &forward_variance[0,0], &inc, &forward_factors[0,0], &inc)             # <<<<<<<<<<<<<<
 *         dpotrf("L", &k_endog, &forward_factors[0,0], &k_endog, &info)
 *         dcopy(&k_endog2, &backward_variance[0,0], &inc, &backward_factors[0,0], &inc)
 */
    __pyx_t_103 = 0;
    __pyx_t_104 = 0;
    __pyx_t_105 = 0;
    __pyx_t_106 = 0;
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dcopy((&__pyx_v_k_endog2), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_forward_variance.data) + __pyx_t_103)) ) + __pyx_t_104 * __pyx_v_forward_variance.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_forward_factors.data) + __pyx_t_105)) ) + __pyx_t_106 * __pyx_v_forward_factors.strides[1]) )))), (&__pyx_v_inc));

    /* "statsmodels\tsa\statespace\_statespace.pyx":5860
 *         # backward_factors =  linalg.cholesky(backward_variance, lower=True)
 *         dcopy(&k_endog2, &forward_variance[0,0], &inc, &forward_factors[0,0], &inc)
 *         dpotrf("L", &k_endog, &forward_factors[0,0], &k_endog, &info)             # <<<<<<<<<<<<<<
 *         dcopy(&k_endog2, &backward_variance[0,0], &inc, &backward_factors[0,0], &inc)
 *         dpotrf("L", &k_endog, &backward_factors[0,0], &k_endog, &info)
 */
    __pyx_t_107 = 0;
    __pyx_t_108 = 0;
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dpotrf(__pyx_k_L, (&__pyx_v_k_endog), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_forward_factors.data) + __pyx_t_107)) ) + __pyx_t_108 * __pyx_v_forward_factors.strides[1]) )))), (&__pyx_v_k_endog), (&__pyx_v_info));

    /* "statsmodels\tsa\statespace\_statespace.pyx":5861
 *         dcopy(&k_endog2, &forward_variance[0,0], &inc, &forward_factors[0,0], &inc)
 *         dpotrf("L", &k_endog, &forward_factors[0,0], &k_endog, &info)
 *         dcopy(&k_endog2, &backward_variance[0,0], &inc, &backward_factors[0,0], &inc)             # <<<<<<<<<<<<<<
 *         dpotrf("L", &k_endog, &backward_factors[0,0], &k_endog, &info)
 * 
 */
    __pyx_t_109 = 0;
    __pyx_t_110 = 0;
    __pyx_t_111 = 0;
    __pyx_t_112 = 0;
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dcopy((&__pyx_v_k_endog2), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_backward_variance.data) + __pyx_t_109)) ) + __pyx_t_110 * __pyx_v_backward_variance.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_backward_factors.data) + __pyx_t_111)) ) + __pyx_t_112 * __pyx_v_backward_factors.strides[1]) )))), (&__pyx_v_inc));

    /* "statsmodels\tsa\statespace\_statespace.pyx":5862
 *         dpotrf("L", &k_endog, &forward_factors[0,0], &k_endog, &info)
 *         dcopy(&k_endog2, &backward_variance[0,0], &inc, &backward_factors[0,0], &inc)
 *         dpotrf("L", &k_endog, &backward_factors[0,0], &k_endog, &info)             # <<<<<<<<<<<<<<
 * 
 * 
 */
    __pyx_t_113 = 0;
    __pyx_t_114 = 0;
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dpotrf(__pyx_k_L, (&__pyx_v_k_endog), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_backward_factors.data) + __pyx_t_113)) ) + __pyx_t_114 * __pyx_v_backward_factors.strides[1]) )))), (&__pyx_v_k_endog), (&__pyx_v_info));
  }

  /* "statsmodels\tsa\statespace\_statespace.pyx":5867
 *     # If we do not want to use the transformed variance, we need to
 *     # adjust the constrained matrices, as presented in Lemma 2.3, see above
 *     if not transform_variance:             # <<<<<<<<<<<<<<
 *         if order % 2 == 0:
 *             forwards = &forwards2[0,0]
 */
  __pyx_t_3 = ((!(__pyx_v_transform_variance != 0)) != 0);
  if (__pyx_t_3) {

    /* "statsmodels\tsa\statespace\_statespace.pyx":5868
 *     # adjust the constrained matrices, as presented in Lemma 2.3, see above
 *     if not transform_variance:
 *         if order % 2 == 0:             # <<<<<<<<<<<<<<
 *             forwards = &forwards2[0,0]
 *         else:
 */
    __pyx_t_3 = ((__Pyx_mod_long(__pyx_v_order, 2) == 0) != 0);
    if (__pyx_t_3) {

      /* "statsmodels\tsa\statespace\_statespace.pyx":5869
 *     if not transform_variance:
 *         if order % 2 == 0:
 *             forwards = &forwards2[0,0]             # <<<<<<<<<<<<<<
 *         else:
 *             forwards = &forwards1[0,0]
 */
      __pyx_t_115 = 0;
      __pyx_t_116 = 0;
      __pyx_v_forwards = (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_forwards2.data) + __pyx_t_115)) ) + __pyx_t_116 * __pyx_v_forwards2.strides[1]) ))));
      goto __pyx_L16;
    }
    /*else*/ {

      /* "statsmodels\tsa\statespace\_statespace.pyx":5871
 *             forwards = &forwards2[0,0]
 *         else:
 *             forwards = &forwards1[0,0]             # <<<<<<<<<<<<<<
 * 
 *         # Here, we need to construct T such that:
 */
      __pyx_t_117 = 0;
      __pyx_t_118 = 0;
      __pyx_v_forwards = (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_forwards1.data) + __pyx_t_117)) ) + __pyx_t_118 * __pyx_v_forwards1.strides[1]) ))));
    }
    __pyx_L16:;

    /* "statsmodels\tsa\statespace\_statespace.pyx":5882
 *         # initial_variance_factor = np.linalg.cholesky(initial_variance)
 *         # L'
 *         dpotrf("U", &k_endog, &initial_variance[0,0], &k_endog, &info)             # <<<<<<<<<<<<<<
 *         # transformed_variance_factor = np.linalg.cholesky(variance)
 *         # M'
 */
    if (unlikely(!__pyx_v_initial_variance.memview)) { __Pyx_RaiseUnboundLocalError("initial_variance"); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 5882; __pyx_clineno = __LINE__; goto __pyx_L1_error;} }
    __pyx_t_119 = 0;
    __pyx_t_120 = 0;
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dpotrf(__pyx_k_U, (&__pyx_v_k_endog), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_initial_variance.data) + __pyx_t_119)) ) + __pyx_t_120 * __pyx_v_initial_variance.strides[1]) )))), (&__pyx_v_k_endog), (&__pyx_v_info));

    /* "statsmodels\tsa\statespace\_statespace.pyx":5885
 *         # transformed_variance_factor = np.linalg.cholesky(variance)
 *         # M'
 *         dcopy(&k_endog2, &forward_variance[0,0], &inc, &tmp[0,0], &inc)             # <<<<<<<<<<<<<<
 *         dpotrf("U", &k_endog, &tmp[0,0], &k_endog, &info)
 *         # dpotri("L", &k_endog, &tmp[0,0], &k_endog, &info)
 */
    __pyx_t_121 = 0;
    __pyx_t_122 = 0;
    __pyx_t_123 = 0;
    __pyx_t_124 = 0;
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dcopy((&__pyx_v_k_endog2), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_forward_variance.data) + __pyx_t_121)) ) + __pyx_t_122 * __pyx_v_forward_variance.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_tmp.data) + __pyx_t_123)) ) + __pyx_t_124 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_inc));

    /* "statsmodels\tsa\statespace\_statespace.pyx":5886
 *         # M'
 *         dcopy(&k_endog2, &forward_variance[0,0], &inc, &tmp[0,0], &inc)
 *         dpotrf("U", &k_endog, &tmp[0,0], &k_endog, &info)             # <<<<<<<<<<<<<<
 *         # dpotri("L", &k_endog, &tmp[0,0], &k_endog, &info)
 * 
 */
    __pyx_t_125 = 0;
    __pyx_t_126 = 0;
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_dpotrf(__pyx_k_U, (&__pyx_v_k_endog), (&(*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_tmp.data) + __pyx_t_125)) ) + __pyx_t_126 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_k_endog), (&__pyx_v_info));

    /* "statsmodels\tsa\statespace\_statespace.pyx":5891
 *         # We need to zero out the lower triangle of L', because ?trtrs only
 *         # knows that M' is upper triangular
 *         for s in range(k_endog - 1):          # column             # <<<<<<<<<<<<<<
 *             for k in range(s+1, k_endog):     # row
 *                 initial_variance[k, s] = 0
 */
    __pyx_t_127 = (__pyx_v_k_endog - 1);
    for (__pyx_t_31 = 0; __pyx_t_31 < __pyx_t_127; __pyx_t_31+=1) {
      __pyx_v_s = __pyx_t_31;

      /* "statsmodels\tsa\statespace\_statespace.pyx":5892
 *         # knows that M' is upper triangular
 *         for s in range(k_endog - 1):          # column
 *             for k in range(s+1, k_endog):     # row             # <<<<<<<<<<<<<<
 *                 initial_variance[k, s] = 0
 * 
 */
      __pyx_t_32 = __pyx_v_k_endog;
      for (__pyx_t_50 = (__pyx_v_s + 1); __pyx_t_50 < __pyx_t_32; __pyx_t_50+=1) {
        __pyx_v_k = __pyx_t_50;

        /* "statsmodels\tsa\statespace\_statespace.pyx":5893
 *         for s in range(k_endog - 1):          # column
 *             for k in range(s+1, k_endog):     # row
 *                 initial_variance[k, s] = 0             # <<<<<<<<<<<<<<
 * 
 *         # Note that T is lower triangular
 */
        if (unlikely(!__pyx_v_initial_variance.memview)) { __Pyx_RaiseUnboundLocalError("initial_variance"); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 5893; __pyx_clineno = __LINE__; goto __pyx_L1_error;} }
        __pyx_t_76 = __pyx_v_k;
        __pyx_t_128 = __pyx_v_s;
        *((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_5numpy_float64_t *) __pyx_v_initial_variance.data) + __pyx_t_76)) ) + __pyx_t_128 * __pyx_v_initial_variance.strides[1]) )) = 0.0;
      }
    }

    /* "statsmodels\tsa\statespace\_statespace.pyx":5900
 *         # transform = np.dot(initial_variance_factor,
 *         #                    np.linalg.inv(transformed_variance_factor))
 *         dtrtrs("U", "N", "N", &k_endog, &k_endog, &tmp[0,0], &k_endog,             # <<<<<<<<<<<<<<
 *                                                            &initial_variance[0, 0], &k_endog, &info)
 *         # Now:
 */
    __pyx_t_129 = 0;
    __pyx_t_130 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":5901
 *         #                    np.linalg.inv(transformed_variance_factor))
 *         dtrtrs("U", "N", "N", &k_endog, &k_endog, &tmp[0,0], &k_endog,
 *                                                            &initial_variance[0, 0], &k_endog, &info)             # <<<<<<<<<<<<<<
 *         # Now:
 *         # initial_variance = T'
 */
    if (unlikely(!__pyx_v_initial_variance.memview)) { __Pyx_RaiseUnboundLocalError("initial_variance"); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 5901; __pyx_clineno = __LINE__; goto __pyx_L1_error;} }
    __pyx_t_131 = 0;
    __pyx_t_132 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":5900
 *         # transform = np.dot(initial_variance_factor,
 *         #                    np.linalg.inv(transformed_variance_factor))
 *         dtrtrs("U", "N", "N", &k_endog, &k_endog, &tmp[0,0], &k_endog,             # <<<<<<<<<<<<<<
 *                                                            &initial_variance[0, 0], &k_endog, &info)
 *         # Now:
 */
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  __pyx_v_beta = __pyx_t_float_complex_from_parts(0.0, 0);

  /* "statsmodels\tsa\statespace\_statespace.pyx":6344
 *         np.complex64_t alpha = 1.0
 *         np.complex64_t beta = 0.0
 *         np.complex64_t gamma = -1.0             # <<<<<<<<<<<<<<
 * 
 *     # #### Forecast for time t
 */
  __pyx_v_gamma = __pyx_t_float_complex_from_parts(-1.0, 0);

  /* "statsmodels\tsa\statespace\_statespace.pyx":6353
 * 
 *     # $\\# = d_t$
 *     ccopy(&kfilter.k_endog, kfilter._obs_intercept, &inc, kfilter._forecast, &inc)             # <<<<<<<<<<<<<<
 *     # `forecast` $= 1.0 * Z_t a_t + 1.0 * \\#$
 *     # $(p \times 1) = (p \times m) (m \times 1) + (p \times 1)$
 */
  __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_ccopy((&__pyx_v_kfilter->k_endog), __pyx_v_kfilter->_obs_intercept, (&__pyx_v_inc), __pyx_v_kfilter->_forecast, (&__pyx_v_inc));

  /* "statsmodels\tsa\statespace\_statespace.pyx":6356
 *     # `forecast` $= 1.0 * Z_t a_t + 1.0 * \\#$
 *     # $(p \times 1) = (p \times m) (m \times 1) + (p \times 1)$
 *     cgemv("N", &kfilter.k_endog, &kfilter.k_states,             # <<<<<<<<<<<<<<
 *           &alpha, kfilter._design, &kfilter.k_endog,
 *                   kfilter._input_state, &inc,
 */
  __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_cgemv(__pyx_k_N, (&__pyx_v_kfilter->k_endog), (&__pyx_v_kfilter->k_states), (&__pyx_v_alpha), __pyx_v_kfilter->_design, (&__pyx_v_kfilter->k_endog), __pyx_v_kfilter->_input_state, (&__pyx_v_inc), (&__pyx_v_alpha), __pyx_v_kfilter->_forecast, (&__pyx_v_inc));

  /* "statsmodels\tsa\statespace\_statespace.pyx":6365
 * 
 *     # $\\# = y_t$
 *     ccopy(&kfilter.k_endog, kfilter._obs, &inc, kfilter._forecast_error, &inc)             # <<<<<<<<<<<<<<
 *     # $v_t = -1.0 * $ `forecast` $ + \\#$
 *     # $(p \times 1) = (p \times 1) + (p \times 1)$
 */
  __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_ccopy((&__pyx_v_kfilter->k_endog), __pyx_v_kfilter->_obs, (&__pyx_v_inc), __pyx_v_kfilter->_forecast_error, (&__pyx_v_inc));

  /* "statsmodels\tsa\statespace\_statespace.pyx":6368
 *     # $v_t = -1.0 * $ `forecast` $ + \\#$
 *     # $(p \times 1) = (p \times 1) + (p \times 1)$
 *     caxpy(&kfilter.k_endog, &gamma, kfilter._forecast, &inc, kfilter._forecast_error, &inc)             # <<<<<<<<<<<<<<
 * 
 *     # *Intermediate calculation* (used just below and then once more)
 */
  __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_caxpy((&__pyx_v_kfilter->k_endog), (&__pyx_v_gamma), __pyx_v_kfilter->_forecast, (&__pyx_v_inc), __pyx_v_kfilter->_forecast_error, (&__pyx_v_inc));

  /* "statsmodels\tsa\statespace\_statespace.pyx":6374
 *     # $\\#_1 = P_t Z_t'$
 *     # $(m \times p) = (m \times m) (p \times m)'$
 *     cgemm("N", "T", &kfilter.k_states, &kfilter.k_endog, &kfilter.k_states,             # <<<<<<<<<<<<<<
 *           &alpha, kfilter._input_state_cov, &kfilter.k_states,
 *                   kfilter._design, &kfilter.k_endog,
 */
  __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_cgemm(__pyx_k_N, __pyx_k_T, (&__pyx_v_kfilter->k_states), (&__pyx_v_kfilter->k_endog), (&__pyx_v_kfilter->k_states), (&__pyx_v_alpha), __pyx_v_kfilter->_input_state_cov, (&__pyx_v_kfilter->k_states), __pyx_v_kfilter->_design, (&__pyx_v_kfilter->k_endog), (&__pyx_v_beta), __pyx_v_kfilter->_tmp1, (&__pyx_v_kfilter->k_states));

  /* "statsmodels\tsa\statespace\_statespace.pyx":6384
 *     # *Note*: this and does nothing at all to `forecast_error_cov` if
 *     # converged == True
 *     if not kfilter.converged:             # <<<<<<<<<<<<<<
 *         # $\\# = H_t$
 *         ccopy(&kfilter.k_endog2, kfilter._obs_cov, &inc, kfilter._forecast_error_cov, &inc)
 */
  __pyx_t_1 = ((!(__pyx_v_kfilter->converged != 0)) != 0);
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    /* "statsmodels\tsa\statespace\_statespace.pyx":6386
 *     if not kfilter.converged:
 *         # $\\# = H_t$
 *         ccopy(&kfilter.k_endog2, kfilter._obs_cov, &inc, kfilter._forecast_error_cov, &inc)             # <<<<<<<<<<<<<<
 * 
 *         # $F_t = 1.0 * Z_t \\#_1 + 1.0 * \\#$
 */
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    /* "statsmodels\tsa\statespace\_statespace.pyx":6389
 * 
 *         # $F_t = 1.0 * Z_t \\#_1 + 1.0 * \\#$
 *         cgemm("N", "N", &kfilter.k_endog, &kfilter.k_endog, &kfilter.k_states,             # <<<<<<<<<<<<<<
 *               &alpha, kfilter._design, &kfilter.k_endog,
 *                      kfilter._tmp1, &kfilter.k_states,
 */
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  /* "statsmodels\tsa\statespace\_statespace.pyx":6394
 *               &alpha, kfilter._forecast_error_cov, &kfilter.k_endog)
 * 
 *     return 0             # <<<<<<<<<<<<<<
 * 
 * cdef int cupdating_conventional(cKalmanFilter kfilter):
 */
  __pyx_r = 0;
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  /* "statsmodels\tsa\statespace\_statespace.pyx":6337
 * # See Durbin and Koopman (2012) Chapter 4
 * 
 * cdef int cforecast_conventional(cKalmanFilter kfilter):             # <<<<<<<<<<<<<<
 * 
 *     # Constants
 */

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/* "statsmodels\tsa\statespace\_statespace.pyx":6396
 *     return 0
 * 
 * cdef int cupdating_conventional(cKalmanFilter kfilter):             # <<<<<<<<<<<<<<
 *     # Constants
 *     cdef:
 */

static int __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_cupdating_conventional(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_kfilter) {
  int __pyx_v_inc;
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 *         np.complex64_t alpha = 1.0
 *         np.complex64_t beta = 0.0
 */
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  /* "statsmodels\tsa\statespace\_statespace.pyx":6400
 *     cdef:
 *         int inc = 1
 *         np.complex64_t alpha = 1.0             # <<<<<<<<<<<<<<
 *         np.complex64_t beta = 0.0
 *         np.complex64_t gamma = -1.0
 */
  __pyx_v_alpha = __pyx_t_float_complex_from_parts(1.0, 0);

  /* "statsmodels\tsa\statespace\_statespace.pyx":6401
 *         int inc = 1
 *         np.complex64_t alpha = 1.0
 *         np.complex64_t beta = 0.0             # <<<<<<<<<<<<<<
 *         np.complex64_t gamma = -1.0
 * 
 */
  __pyx_v_beta = __pyx_t_float_complex_from_parts(0.0, 0);

  /* "statsmodels\tsa\statespace\_statespace.pyx":6402
 *         np.complex64_t alpha = 1.0
 *         np.complex64_t beta = 0.0
 *         np.complex64_t gamma = -1.0             # <<<<<<<<<<<<<<
 * 
 *     # #### Filtered state for time t
 */
  __pyx_v_gamma = __pyx_t_float_complex_from_parts(-1.0, 0);

  /* "statsmodels\tsa\statespace\_statespace.pyx":6407
 *     # $a_{t|t} = a_t + P_t Z_t' F_t^{-1} v_t$
 *     # $a_{t|t} = 1.0 * \\#_1 \\#_2 + 1.0 a_t$
 *     ccopy(&kfilter.k_states, kfilter._input_state, &inc, kfilter._filtered_state, &inc)             # <<<<<<<<<<<<<<
 *     cgemv("N", &kfilter.k_states, &kfilter.k_endog,
 *           &alpha, kfilter._tmp1, &kfilter.k_states,
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  __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_ccopy((&__pyx_v_kfilter->k_states), __pyx_v_kfilter->_input_state, (&__pyx_v_inc), __pyx_v_kfilter->_filtered_state, (&__pyx_v_inc));

  /* "statsmodels\tsa\statespace\_statespace.pyx":6408
 *     # $a_{t|t} = 1.0 * \\#_1 \\#_2 + 1.0 a_t$
 *     ccopy(&kfilter.k_states, kfilter._input_state, &inc, kfilter._filtered_state, &inc)
 *     cgemv("N", &kfilter.k_states, &kfilter.k_endog,             # <<<<<<<<<<<<<<
 *           &alpha, kfilter._tmp1, &kfilter.k_states,
 *                   kfilter._tmp2, &inc,
 */
  __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_cgemv(__pyx_k_N, (&__pyx_v_kfilter->k_states), (&__pyx_v_kfilter->k_endog), (&__pyx_v_alpha), __pyx_v_kfilter->_tmp1, (&__pyx_v_kfilter->k_states), __pyx_v_kfilter->_tmp2, (&__pyx_v_inc), (&__pyx_v_alpha), __pyx_v_kfilter->_filtered_state, (&__pyx_v_inc));

  /* "statsmodels\tsa\statespace\_statespace.pyx":6419
 *     # *Note*: this and does nothing at all to `filtered_state_cov` if
 *     # converged == True
 *     if not kfilter.converged:             # <<<<<<<<<<<<<<
 *         ccopy(&kfilter.k_states2, kfilter._input_state_cov, &inc, kfilter._filtered_state_cov, &inc)
 * 
 */
  __pyx_t_1 = ((!(__pyx_v_kfilter->converged != 0)) != 0);
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    /* "statsmodels\tsa\statespace\_statespace.pyx":6420
 *     # converged == True
 *     if not kfilter.converged:
 *         ccopy(&kfilter.k_states2, kfilter._input_state_cov, &inc, kfilter._filtered_state_cov, &inc)             # <<<<<<<<<<<<<<
 * 
 *         # `tmp0` array used here, dimension $(m \times m)$
 */
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_ccopy((&__pyx_v_kfilter->k_states2), __pyx_v_kfilter->_input_state_cov, (&__pyx_v_inc), __pyx_v_kfilter->_filtered_state_cov, (&__pyx_v_inc));

    /* "statsmodels\tsa\statespace\_statespace.pyx":6425
 *         # $\\#_0 = 1.0 * \\#_1 \\#_3$
 *         # $(m \times m) = (m \times p) (p \times m)$
 *         cgemm("N", "N", &kfilter.k_states, &kfilter.k_states, &kfilter.k_endog,             # <<<<<<<<<<<<<<
 *               &alpha, kfilter._tmp1, &kfilter.k_states,
 *                       kfilter._tmp3, &kfilter.k_endog,
 */
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_cgemm(__pyx_k_N, __pyx_k_N, (&__pyx_v_kfilter->k_states), (&__pyx_v_kfilter->k_states), (&__pyx_v_kfilter->k_endog), (&__pyx_v_alpha), __pyx_v_kfilter->_tmp1, (&__pyx_v_kfilter->k_states), __pyx_v_kfilter->_tmp3, (&__pyx_v_kfilter->k_endog), (&__pyx_v_beta), __pyx_v_kfilter->_tmp0, (&__pyx_v_kfilter->k_states));

    /* "statsmodels\tsa\statespace\_statespace.pyx":6432
 *         # $P_{t|t} = - 1.0 * \\# P_t + 1.0 * P_t$
 *         # $(m \times m) = (m \times m) (m \times m) + (m \times m)$
 *         cgemm("N", "N", &kfilter.k_states, &kfilter.k_states, &kfilter.k_states,             # <<<<<<<<<<<<<<
 *               &gamma, kfilter._tmp0, &kfilter.k_states,
 *                       kfilter._input_state_cov, &kfilter.k_states,
 */
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_cgemm(__pyx_k_N, __pyx_k_N, (&__pyx_v_kfilter->k_states), (&__pyx_v_kfilter->k_states), (&__pyx_v_kfilter->k_states), (&__pyx_v_gamma), __pyx_v_kfilter->_tmp0, (&__pyx_v_kfilter->k_states), __pyx_v_kfilter->_input_state_cov, (&__pyx_v_kfilter->k_states), (&__pyx_v_alpha), __pyx_v_kfilter->_filtered_state_cov, (&__pyx_v_kfilter->k_states));
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  __pyx_L3:;

  /* "statsmodels\tsa\statespace\_statespace.pyx":6437
 *               &alpha, kfilter._filtered_state_cov, &kfilter.k_states)
 * 
 *     return 0             # <<<<<<<<<<<<<<
 * 
 * cdef int cprediction_conventional(cKalmanFilter kfilter):
 */
  __pyx_r = 0;
  goto __pyx_L0;

  /* "statsmodels\tsa\statespace\_statespace.pyx":6396
 *     return 0
 * 
 * cdef int cupdating_conventional(cKalmanFilter kfilter):             # <<<<<<<<<<<<<<
 *     # Constants
 *     cdef:
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/* "statsmodels\tsa\statespace\_statespace.pyx":6439
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 * 
 * cdef int cprediction_conventional(cKalmanFilter kfilter):             # <<<<<<<<<<<<<<
 * 
 *     # Constants
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static int __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_cprediction_conventional(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_kfilter) {
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 *         np.complex64_t alpha = 1.0
 *         np.complex64_t beta = 0.0
 */
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 *     cdef:
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 *         np.complex64_t alpha = 1.0             # <<<<<<<<<<<<<<
 *         np.complex64_t beta = 0.0
 *         np.complex64_t gamma = -1.0
 */
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  /* "statsmodels\tsa\statespace\_statespace.pyx":6445
 *         int inc = 1
 *         np.complex64_t alpha = 1.0
 *         np.complex64_t beta = 0.0             # <<<<<<<<<<<<<<
 *         np.complex64_t gamma = -1.0
 * 
 */
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  /* "statsmodels\tsa\statespace\_statespace.pyx":6446
 *         np.complex64_t alpha = 1.0
 *         np.complex64_t beta = 0.0
 *         np.complex64_t gamma = -1.0             # <<<<<<<<<<<<<<
 * 
 *     # #### Predicted state for time t+1
 */
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  /* "statsmodels\tsa\statespace\_statespace.pyx":6450
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 *     # $a_{t+1} = T_t a_{t|t} + c_t$
 *     ccopy(&kfilter.k_states, kfilter._state_intercept, &inc, kfilter._predicted_state, &inc)             # <<<<<<<<<<<<<<
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  /* "statsmodels\tsa\statespace\_statespace.pyx":6451
 *     # $a_{t+1} = T_t a_{t|t} + c_t$
 *     ccopy(&kfilter.k_states, kfilter._state_intercept, &inc, kfilter._predicted_state, &inc)
 *     cgemv("N", &kfilter.k_states, &kfilter.k_states,             # <<<<<<<<<<<<<<
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 */
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  /* "statsmodels\tsa\statespace\_statespace.pyx":6461
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 *     # converged == True
 *     if not kfilter.converged:             # <<<<<<<<<<<<<<
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 *     if not kfilter.converged:
 *         ccopy(&kfilter.k_states2, kfilter._selected_state_cov, &inc, kfilter._predicted_state_cov, &inc)             # <<<<<<<<<<<<<<
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 *         # $(m \times m) = (m \times m) (m \times m)$
 *         cgemm("N", "N", &kfilter.k_states, &kfilter.k_states, &kfilter.k_states,             # <<<<<<<<<<<<<<
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 *         # $(m \times m) = (m \times m) (m \times m) + (m \times m)$
 *         cgemm("N", "T", &kfilter.k_states, &kfilter.k_states, &kfilter.k_states,             # <<<<<<<<<<<<<<
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 * 
 *     return 0             # <<<<<<<<<<<<<<
 * 
 * 
 */
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 * 
 * cdef int cprediction_conventional(cKalmanFilter kfilter):             # <<<<<<<<<<<<<<
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 *     # Constants
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/* "statsmodels\tsa\statespace\_statespace.pyx":6482
 * 
 * 
 * cdef np.complex64_t cloglikelihood_conventional(cKalmanFilter kfilter, np.complex64_t determinant):             # <<<<<<<<<<<<<<
 *     # Constants
 *     cdef:
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 *     """
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 * 
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 *         # 0.11.0, we can't use them, so we must fill in the lower triangle
 *         # by hand
 *         for i in range(kfilter.k_endog):             # <<<<<<<<<<<<<<
 *             for j in range(i):
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 *         # by hand
 *         for i in range(kfilter.k_endog):
 *             for j in range(i):             # <<<<<<<<<<<<<<
 *                 kfilter._forecast_error_fac[i + j*kfilter.k_endog] = kfilter._forecast_error_fac[j + i*kfilter.k_endog]
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 */
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 *         for i in range(kfilter.k_endog):
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 * 
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 *     #csymv("U", &kfilter.k_endog, &alpha, kfilter._forecast_error_fac, &kfilter.k_endog,
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 *                    &beta, kfilter._tmp3, &kfilter.k_endog)
 * 
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 * 
 * cdef np.complex64_t cinverse_lu(cKalmanFilter kfilter, np.complex64_t determinant) except *:
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 *     return determinant
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/* "statsmodels\tsa\statespace\_statespace.pyx":6675
 *     return determinant
 * 
 * cdef np.complex64_t cinverse_lu(cKalmanFilter kfilter, np.complex64_t determinant) except *:             # <<<<<<<<<<<<<<
 *     """
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 *         int info
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 *         np.complex64_t beta = 0.0
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 */
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 *         int inc = 1
 *         np.complex64_t alpha = 1.0
 *         np.complex64_t beta = 0.0             # <<<<<<<<<<<<<<
 * 
 *     if not kfilter.converged:
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 *         np.complex64_t beta = 0.0
 * 
 *     if not kfilter.converged:             # <<<<<<<<<<<<<<
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 *     if not kfilter.converged:
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 * 
 *         # Continue taking the inverse
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 *     # `tmp2` array used here, dimension $(p \times 1)$
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 *     # `tmp3` array used here, dimension $(p \times m)$
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 * 
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 *                 l = 0
 *                 for j in range(self.model.k_endog):
 *                     if not self.model.missing[j, self.t]:             # <<<<<<<<<<<<<<
 *                         self.selected_obs_cov[l + k*self.k_endog] = self.model.obs_cov[j, i, obs_cov_t]
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          /* "statsmodels\tsa\statespace\_statespace.pyx":7444
 *                 for j in range(self.model.k_endog):
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 *                         l += 1
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          /* "statsmodels\tsa\statespace\_statespace.pyx":7445
 *                     if not self.model.missing[j, self.t]:
 *                         self.selected_obs_cov[l + k*self.k_endog] = self.model.obs_cov[j, i, obs_cov_t]
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 *                         self.selected_obs_cov[l + k*self.k_endog] = self.model.obs_cov[j, i, obs_cov_t]
 *                         l += 1
 *                 k += 1             # <<<<<<<<<<<<<<
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 *                         l += 1
 *                 k += 1
 *         self._obs = &self.selected_obs[0]             # <<<<<<<<<<<<<<
 *         self._design = &self.selected_design[0]
 *         self._obs_cov = &self.selected_obs_cov[0]
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 *                 k += 1
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 *         self._design = &self.selected_design[0]             # <<<<<<<<<<<<<<
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 */
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 *         self._design = &self.selected_design[0]
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 *     cdef void post_convergence(self):
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  /* "statsmodels\tsa\statespace\_statespace.pyx":7409
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 * 
 *     cdef void _select_missing_partial_obs(self):             # <<<<<<<<<<<<<<
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/* "statsmodels\tsa\statespace\_statespace.pyx":7451
 *         self._obs_cov = &self.selected_obs_cov[0]
 * 
 *     cdef void post_convergence(self):             # <<<<<<<<<<<<<<
 *         # TODO this should probably be defined separately for each Kalman filter type - e.g. `post_convergence_conventional`, etc.
 * 
 */

static void __pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_post_convergence(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *__pyx_v_self) {
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 * 
 *         if self.converged:
 */
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  /* "statsmodels\tsa\statespace\_statespace.pyx":7458
 *             int inc = 1
 * 
 *         if self.converged:             # <<<<<<<<<<<<<<
 *             # $F_t$
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    /* "statsmodels\tsa\statespace\_statespace.pyx":7460
 *         if self.converged:
 *             # $F_t$
 *             ccopy(&self.k_endog2, self._converged_forecast_error_cov, &inc, self._forecast_error_cov, &inc)             # <<<<<<<<<<<<<<
 *             # $P_{t|t}$
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    /* "statsmodels\tsa\statespace\_statespace.pyx":7462
 *             ccopy(&self.k_endog2, self._converged_forecast_error_cov, &inc, self._forecast_error_cov, &inc)
 *             # $P_{t|t}$
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 *             # $P_t$
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 *             ccopy(&self.k_states2, self._converged_filtered_state_cov, &inc, self._filtered_state_cov, &inc)
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    /* "statsmodels\tsa\statespace\_statespace.pyx":7466
 *             ccopy(&self.k_states2, self._converged_predicted_state_cov, &inc, self._predicted_state_cov, &inc)
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 *         self._obs_cov = &self.selected_obs_cov[0]
 * 
 *     cdef void post_convergence(self):             # <<<<<<<<<<<<<<
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/* "statsmodels\tsa\statespace\_statespace.pyx":7468
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 * 
 *     cdef void numerical_stability(self):             # <<<<<<<<<<<<<<
 *         cdef int i, j
 *         cdef int predicted_t = self.t
 */

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  int __pyx_t_6;
  int __pyx_t_7;
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 *         cdef np.complex64_t value
 * 
 */
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 * 
 *         if self.conserve_memory & MEMORY_NO_PREDICTED:             # <<<<<<<<<<<<<<
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 */
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 * 
 *         if self.stability_method & STABILITY_FORCE_SYMMETRY:             # <<<<<<<<<<<<<<
 *             # Enforce symmetry of predicted covariance matrix
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  __pyx_t_2 = ((__pyx_v_self->stability_method & __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_STABILITY_FORCE_SYMMETRY) != 0);
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 *             # $P_{t+1} = 0.5 * (P_{t+1} + P_{t+1}')$
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 *             for i in range(self.k_states):             # <<<<<<<<<<<<<<
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 *             # See Grewal (2001), Section 6.3.1.1
 *             for i in range(self.k_states):
 *                 for j in range(i, self.k_states):             # <<<<<<<<<<<<<<
 *                     value = 0.5 * (
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 *                 for j in range(i, self.k_states):
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        /* "statsmodels\tsa\statespace\_statespace.pyx":7482
 *             for i in range(self.k_states):
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 *                         self.predicted_state_cov[i,j,predicted_t+1] +
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 *                     self.predicted_state_cov[i,j,predicted_t+1] = value             # <<<<<<<<<<<<<<
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 *     cdef void check_convergence(self):
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 *         if self.time_invariant and not self.converged and self.model.nmissing[self.t] == 0:             # <<<<<<<<<<<<<<
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 * 
 *             cgemv("N", &inc, &self.k_states2, &alpha, self._tmp0, &inc, self._tmp0, &inc, &beta, self._tmp1, &inc)
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 */
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 *         # Forecast: 1 -> 0
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 *             ccopy(&self.k_endog, &self.forecast[0, 1], &inc, &self.forecast[0, 0], &inc)
 *             ccopy(&self.k_endog, &self.forecast_error[0, 1], &inc, &self.forecast_error[0, 0], &inc)
 */
  __pyx_t_1 = (((__pyx_v_self->conserve_memory & __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_MEMORY_NO_FORECAST) > 0) != 0);
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    /* "statsmodels\tsa\statespace\_statespace.pyx":7538
 *         # Forecast: 1 -> 0
 *         if self.conserve_memory & MEMORY_NO_FORECAST > 0:
 *             ccopy(&self.k_endog, &self.forecast[0, 1], &inc, &self.forecast[0, 0], &inc)             # <<<<<<<<<<<<<<
 *             ccopy(&self.k_endog, &self.forecast_error[0, 1], &inc, &self.forecast_error[0, 0], &inc)
 *             ccopy(&self.k_endog2, &self.forecast_error_cov[0, 0, 1], &inc, &self.forecast_error_cov[0, 0, 0], &inc)
 */
    if (unlikely(!__pyx_v_self->forecast.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 7538; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
    __pyx_t_2 = 0;
    __pyx_t_3 = 1;
    if (unlikely(!__pyx_v_self->forecast.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 7538; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
    __pyx_t_4 = 0;
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 *         if self.conserve_memory & MEMORY_NO_FORECAST > 0:
 *             ccopy(&self.k_endog, &self.forecast[0, 1], &inc, &self.forecast[0, 0], &inc)
 *             ccopy(&self.k_endog, &self.forecast_error[0, 1], &inc, &self.forecast_error[0, 0], &inc)             # <<<<<<<<<<<<<<
 *             ccopy(&self.k_endog2, &self.forecast_error_cov[0, 0, 1], &inc, &self.forecast_error_cov[0, 0, 0], &inc)
 * 
 */
    if (unlikely(!__pyx_v_self->forecast_error.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 7539; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
    __pyx_t_6 = 0;
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    if (unlikely(!__pyx_v_self->forecast_error.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");{__pyx_filename = __pyx_f[0]; __pyx_lineno = 7539; __pyx_clineno = __LINE__; goto __pyx_L1_error;}}
    __pyx_t_8 = 0;
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    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_ccopy((&__pyx_v_self->k_endog), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_self->forecast_error.data) + __pyx_t_6)) ) + __pyx_t_7 * __pyx_v_self->forecast_error.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_self->forecast_error.data) + __pyx_t_8)) ) + __pyx_t_9 * __pyx_v_self->forecast_error.strides[1]) )))), (&__pyx_v_inc));

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 *             ccopy(&self.k_endog, &self.forecast[0, 1], &inc, &self.forecast[0, 0], &inc)
 *             ccopy(&self.k_endog, &self.forecast_error[0, 1], &inc, &self.forecast_error[0, 0], &inc)
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 *         # Filtered: 1 -> 0
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    __pyx_t_13 = 0;
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  /* "statsmodels\tsa\statespace\_statespace.pyx":7543
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 *         # Filtered: 1 -> 0
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 */
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    __pyx_t_18 = 0;
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    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_ccopy((&__pyx_v_self->k_states), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_self->filtered_state.data) + __pyx_t_16)) ) + __pyx_t_17 * __pyx_v_self->filtered_state.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_self->filtered_state.data) + __pyx_t_18)) ) + __pyx_t_19 * __pyx_v_self->filtered_state.strides[1]) )))), (&__pyx_v_inc));

    /* "statsmodels\tsa\statespace\_statespace.pyx":7545
 *         if self.conserve_memory & MEMORY_NO_FILTERED > 0:
 *             ccopy(&self.k_states, &self.filtered_state[0, 1], &inc, &self.filtered_state[0, 0], &inc)
 *             ccopy(&self.k_states2, &self.filtered_state_cov[0, 0, 1], &inc, &self.filtered_state_cov[0, 0, 0], &inc)             # <<<<<<<<<<<<<<
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 *         # Predicted: 1 -> 0
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    __pyx_t_20 = 0;
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    __pyx_t_23 = 0;
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  /* "statsmodels\tsa\statespace\_statespace.pyx":7548
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    /* "statsmodels\tsa\statespace\_statespace.pyx":7549
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 */
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 *             # Predicted: 2 -> 1
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 *             # Predicted: 2 -> 1
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 * cpdef _ccompute_coefficients_from_multivariate_pacf(np.complex64_t [::1,:] partial_autocorrelations,
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  /* "statsmodels\tsa\statespace\_statespace.pyx":7634
 *     backwards2 = np.PyArray_ZEROS(2, dim2, np.NPY_COMPLEX64, FORTRAN)
 * 
 *     dim2[0] = k_endog; dim2[1] = k_endog_order1;             # <<<<<<<<<<<<<<
 *     autocovariances = np.PyArray_ZEROS(2, dim2, np.NPY_COMPLEX64, FORTRAN)
 * 
 */
  (__pyx_v_dim2[0]) = __pyx_v_k_endog;
  (__pyx_v_dim2[1]) = __pyx_v_k_endog_order1;

  /* "statsmodels\tsa\statespace\_statespace.pyx":7635
 * 
 *     dim2[0] = k_endog; dim2[1] = k_endog_order1;
 *     autocovariances = np.PyArray_ZEROS(2, dim2, np.NPY_COMPLEX64, FORTRAN)             # <<<<<<<<<<<<<<
 * 
 *     ccopy(&k_endog2, &error_variance[0,0], &inc, &forward_variance[0,0], &inc)   # \Sigma_s
 */
  __pyx_t_1 = PyArray_ZEROS(2, __pyx_v_dim2, NPY_COMPLEX64, __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_FORTRAN); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 7635; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
  __Pyx_GOTREF(__pyx_t_1);
  __pyx_t_5 = __Pyx_PyObject_to_MemoryviewSlice_dcd____pyx_t_float_complex(__pyx_t_1);
  if (unlikely(!__pyx_t_5.memview)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 7635; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
  __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
  __pyx_v_autocovariances = __pyx_t_5;
  __pyx_t_5.memview = NULL;
  __pyx_t_5.data = NULL;

  /* "statsmodels\tsa\statespace\_statespace.pyx":7637
 *     autocovariances = np.PyArray_ZEROS(2, dim2, np.NPY_COMPLEX64, FORTRAN)
 * 
 *     ccopy(&k_endog2, &error_variance[0,0], &inc, &forward_variance[0,0], &inc)   # \Sigma_s             # <<<<<<<<<<<<<<
 *     ccopy(&k_endog2, &error_variance[0,0], &inc, &backward_variance[0,0], &inc)  # \Sigma_s^*,  s = 0, ..., p
 *     ccopy(&k_endog2, &error_variance[0,0], &inc, &autocovariances[0,0], &inc)  # \Gamma_s
 */
  __pyx_t_10 = 0;
  __pyx_t_11 = 0;
  __pyx_t_12 = 0;
  __pyx_t_13 = 0;
  __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_ccopy((&__pyx_v_k_endog2), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_error_variance.data) + __pyx_t_10)) ) + __pyx_t_11 * __pyx_v_error_variance.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_forward_variance.data) + __pyx_t_12)) ) + __pyx_t_13 * __pyx_v_forward_variance.strides[1]) )))), (&__pyx_v_inc));

  /* "statsmodels\tsa\statespace\_statespace.pyx":7638
 * 
 *     ccopy(&k_endog2, &error_variance[0,0], &inc, &forward_variance[0,0], &inc)   # \Sigma_s
 *     ccopy(&k_endog2, &error_variance[0,0], &inc, &backward_variance[0,0], &inc)  # \Sigma_s^*,  s = 0, ..., p             # <<<<<<<<<<<<<<
 *     ccopy(&k_endog2, &error_variance[0,0], &inc, &autocovariances[0,0], &inc)  # \Gamma_s
 * 
 */
  __pyx_t_14 = 0;
  __pyx_t_15 = 0;
  __pyx_t_16 = 0;
  __pyx_t_17 = 0;
  __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_ccopy((&__pyx_v_k_endog2), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_error_variance.data) + __pyx_t_14)) ) + __pyx_t_15 * __pyx_v_error_variance.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_backward_variance.data) + __pyx_t_16)) ) + __pyx_t_17 * __pyx_v_backward_variance.strides[1]) )))), (&__pyx_v_inc));

  /* "statsmodels\tsa\statespace\_statespace.pyx":7639
 *     ccopy(&k_endog2, &error_variance[0,0], &inc, &forward_variance[0,0], &inc)   # \Sigma_s
 *     ccopy(&k_endog2, &error_variance[0,0], &inc, &backward_variance[0,0], &inc)  # \Sigma_s^*,  s = 0, ..., p
 *     ccopy(&k_endog2, &error_variance[0,0], &inc, &autocovariances[0,0], &inc)  # \Gamma_s             # <<<<<<<<<<<<<<
 * 
 *     # error_variance_factor = linalg.cholesky(error_variance, lower=True)
 */
  __pyx_t_18 = 0;
  __pyx_t_19 = 0;
  __pyx_t_20 = 0;
  __pyx_t_21 = 0;
  __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_ccopy((&__pyx_v_k_endog2), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_error_variance.data) + __pyx_t_18)) ) + __pyx_t_19 * __pyx_v_error_variance.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_autocovariances.data) + __pyx_t_20)) ) + __pyx_t_21 * __pyx_v_autocovariances.strides[1]) )))), (&__pyx_v_inc));

  /* "statsmodels\tsa\statespace\_statespace.pyx":7642
 * 
 *     # error_variance_factor = linalg.cholesky(error_variance, lower=True)
 *     ccopy(&k_endog2, &error_variance[0,0], &inc, &forward_factors[0,0], &inc)             # <<<<<<<<<<<<<<
 *     cpotrf("L", &k_endog, &forward_factors[0,0], &k_endog, &info)
 *     ccopy(&k_endog2, &forward_factors[0,0], &inc, &backward_factors[0,0], &inc)
 */
  __pyx_t_22 = 0;
  __pyx_t_23 = 0;
  __pyx_t_24 = 0;
  __pyx_t_25 = 0;
  __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_ccopy((&__pyx_v_k_endog2), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_error_variance.data) + __pyx_t_22)) ) + __pyx_t_23 * __pyx_v_error_variance.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_forward_factors.data) + __pyx_t_24)) ) + __pyx_t_25 * __pyx_v_forward_factors.strides[1]) )))), (&__pyx_v_inc));

  /* "statsmodels\tsa\statespace\_statespace.pyx":7643
 *     # error_variance_factor = linalg.cholesky(error_variance, lower=True)
 *     ccopy(&k_endog2, &error_variance[0,0], &inc, &forward_factors[0,0], &inc)
 *     cpotrf("L", &k_endog, &forward_factors[0,0], &k_endog, &info)             # <<<<<<<<<<<<<<
 *     ccopy(&k_endog2, &forward_factors[0,0], &inc, &backward_factors[0,0], &inc)
 * 
 */
  __pyx_t_26 = 0;
  __pyx_t_27 = 0;
  __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_cpotrf(__pyx_k_L, (&__pyx_v_k_endog), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_forward_factors.data) + __pyx_t_26)) ) + __pyx_t_27 * __pyx_v_forward_factors.strides[1]) )))), (&__pyx_v_k_endog), (&__pyx_v_info));

  /* "statsmodels\tsa\statespace\_statespace.pyx":7644
 *     ccopy(&k_endog2, &error_variance[0,0], &inc, &forward_factors[0,0], &inc)
 *     cpotrf("L", &k_endog, &forward_factors[0,0], &k_endog, &info)
 *     ccopy(&k_endog2, &forward_factors[0,0], &inc, &backward_factors[0,0], &inc)             # <<<<<<<<<<<<<<
 * 
 *     # We fill in the entries as follows:
 */
  __pyx_t_28 = 0;
  __pyx_t_29 = 0;
  __pyx_t_30 = 0;
  __pyx_t_31 = 0;
  __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_ccopy((&__pyx_v_k_endog2), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_forward_factors.data) + __pyx_t_28)) ) + __pyx_t_29 * __pyx_v_forward_factors.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_backward_factors.data) + __pyx_t_30)) ) + __pyx_t_31 * __pyx_v_backward_factors.strides[1]) )))), (&__pyx_v_inc));

  /* "statsmodels\tsa\statespace\_statespace.pyx":7653
 *     # [p,p], [p,1], ..., [p,p-1]
 *     # the last row, correctly ordered, is then used as the coefficients
 *     for s in range(order):  # s = 0, ..., p-1             # <<<<<<<<<<<<<<
 *         if s % 2 == 0:
 *             forwards = &forwards1[0, 0]
 */
  __pyx_t_32 = __pyx_v_order;
  for (__pyx_t_33 = 0; __pyx_t_33 < __pyx_t_32; __pyx_t_33+=1) {
    __pyx_v_s = __pyx_t_33;

    /* "statsmodels\tsa\statespace\_statespace.pyx":7654
 *     # the last row, correctly ordered, is then used as the coefficients
 *     for s in range(order):  # s = 0, ..., p-1
 *         if s % 2 == 0:             # <<<<<<<<<<<<<<
 *             forwards = &forwards1[0, 0]
 *             prev_forwards = &forwards2[0, 0]
 */
    __pyx_t_3 = ((__Pyx_mod_long(__pyx_v_s, 2) == 0) != 0);
    if (__pyx_t_3) {

      /* "statsmodels\tsa\statespace\_statespace.pyx":7655
 *     for s in range(order):  # s = 0, ..., p-1
 *         if s % 2 == 0:
 *             forwards = &forwards1[0, 0]             # <<<<<<<<<<<<<<
 *             prev_forwards = &forwards2[0, 0]
 *             backwards = &backwards1[0, 0]
 */
      __pyx_t_34 = 0;
      __pyx_t_35 = 0;
      __pyx_v_forwards = (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_forwards1.data) + __pyx_t_34)) ) + __pyx_t_35 * __pyx_v_forwards1.strides[1]) ))));

      /* "statsmodels\tsa\statespace\_statespace.pyx":7656
 *         if s % 2 == 0:
 *             forwards = &forwards1[0, 0]
 *             prev_forwards = &forwards2[0, 0]             # <<<<<<<<<<<<<<
 *             backwards = &backwards1[0, 0]
 *             prev_backwards = &backwards2[0, 0]
 */
      __pyx_t_36 = 0;
      __pyx_t_37 = 0;
      __pyx_v_prev_forwards = (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_forwards2.data) + __pyx_t_36)) ) + __pyx_t_37 * __pyx_v_forwards2.strides[1]) ))));

      /* "statsmodels\tsa\statespace\_statespace.pyx":7657
 *             forwards = &forwards1[0, 0]
 *             prev_forwards = &forwards2[0, 0]
 *             backwards = &backwards1[0, 0]             # <<<<<<<<<<<<<<
 *             prev_backwards = &backwards2[0, 0]
 *         else:
 */
      __pyx_t_38 = 0;
      __pyx_t_39 = 0;
      __pyx_v_backwards = (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_backwards1.data) + __pyx_t_38)) ) + __pyx_t_39 * __pyx_v_backwards1.strides[1]) ))));

      /* "statsmodels\tsa\statespace\_statespace.pyx":7658
 *             prev_forwards = &forwards2[0, 0]
 *             backwards = &backwards1[0, 0]
 *             prev_backwards = &backwards2[0, 0]             # <<<<<<<<<<<<<<
 *         else:
 *             forwards = &forwards2[0, 0]
 */
      __pyx_t_40 = 0;
      __pyx_t_41 = 0;
      __pyx_v_prev_backwards = (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_backwards2.data) + __pyx_t_40)) ) + __pyx_t_41 * __pyx_v_backwards2.strides[1]) ))));
      goto __pyx_L6;
    }
    /*else*/ {

      /* "statsmodels\tsa\statespace\_statespace.pyx":7660
 *             prev_backwards = &backwards2[0, 0]
 *         else:
 *             forwards = &forwards2[0, 0]             # <<<<<<<<<<<<<<
 *             prev_forwards = &forwards1[0, 0]
 *             backwards = &backwards2[0, 0]
 */
      __pyx_t_42 = 0;
      __pyx_t_43 = 0;
      __pyx_v_forwards = (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_forwards2.data) + __pyx_t_42)) ) + __pyx_t_43 * __pyx_v_forwards2.strides[1]) ))));

      /* "statsmodels\tsa\statespace\_statespace.pyx":7661
 *         else:
 *             forwards = &forwards2[0, 0]
 *             prev_forwards = &forwards1[0, 0]             # <<<<<<<<<<<<<<
 *             backwards = &backwards2[0, 0]
 *             prev_backwards = &backwards1[0, 0]
 */
      __pyx_t_44 = 0;
      __pyx_t_45 = 0;
      __pyx_v_prev_forwards = (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_forwards1.data) + __pyx_t_44)) ) + __pyx_t_45 * __pyx_v_forwards1.strides[1]) ))));

      /* "statsmodels\tsa\statespace\_statespace.pyx":7662
 *             forwards = &forwards2[0, 0]
 *             prev_forwards = &forwards1[0, 0]
 *             backwards = &backwards2[0, 0]             # <<<<<<<<<<<<<<
 *             prev_backwards = &backwards1[0, 0]
 * 
 */
      __pyx_t_46 = 0;
      __pyx_t_47 = 0;
      __pyx_v_backwards = (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_backwards2.data) + __pyx_t_46)) ) + __pyx_t_47 * __pyx_v_backwards2.strides[1]) ))));

      /* "statsmodels\tsa\statespace\_statespace.pyx":7663
 *             prev_forwards = &forwards1[0, 0]
 *             backwards = &backwards2[0, 0]
 *             prev_backwards = &backwards1[0, 0]             # <<<<<<<<<<<<<<
 * 
 *         # Create the "last" (k = s+1) matrix
 */
      __pyx_t_48 = 0;
      __pyx_t_49 = 0;
      __pyx_v_prev_backwards = (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_backwards1.data) + __pyx_t_48)) ) + __pyx_t_49 * __pyx_v_backwards1.strides[1]) ))));
    }
    __pyx_L6:;

    /* "statsmodels\tsa\statespace\_statespace.pyx":7677
 *         #         lower=True, trans='T').T
 *         # )
 *         for k in range(k_endog):             # <<<<<<<<<<<<<<
 *             ccopy(&k_endog, &partial_autocorrelations[k,s*k_endog], &k_endog, &tmp[0, k], &inc)
 *         ctrtrs("L", "T", "N", &k_endog, &k_endog, &backward_factors[0,0], &k_endog,
 */
    __pyx_t_50 = __pyx_v_k_endog;
    for (__pyx_t_51 = 0; __pyx_t_51 < __pyx_t_50; __pyx_t_51+=1) {
      __pyx_v_k = __pyx_t_51;

      /* "statsmodels\tsa\statespace\_statespace.pyx":7678
 *         # )
 *         for k in range(k_endog):
 *             ccopy(&k_endog, &partial_autocorrelations[k,s*k_endog], &k_endog, &tmp[0, k], &inc)             # <<<<<<<<<<<<<<
 *         ctrtrs("L", "T", "N", &k_endog, &k_endog, &backward_factors[0,0], &k_endog,
 *                                                            &tmp[0, 0], &k_endog, &info)
 */
      __pyx_t_52 = __pyx_v_k;
      __pyx_t_53 = (__pyx_v_s * __pyx_v_k_endog);
      __pyx_t_54 = 0;
      __pyx_t_55 = __pyx_v_k;
      __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_ccopy((&__pyx_v_k_endog), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_partial_autocorrelations.data) + __pyx_t_52)) ) + __pyx_t_53 * __pyx_v_partial_autocorrelations.strides[1]) )))), (&__pyx_v_k_endog), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_tmp.data) + __pyx_t_54)) ) + __pyx_t_55 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_inc));
    }

    /* "statsmodels\tsa\statespace\_statespace.pyx":7679
 *         for k in range(k_endog):
 *             ccopy(&k_endog, &partial_autocorrelations[k,s*k_endog], &k_endog, &tmp[0, k], &inc)
 *         ctrtrs("L", "T", "N", &k_endog, &k_endog, &backward_factors[0,0], &k_endog,             # <<<<<<<<<<<<<<
 *                                                            &tmp[0, 0], &k_endog, &info)
 *         # cgemm("N", "T", &k_endog, &k_endog, &k_endog,
 */
    __pyx_t_56 = 0;
    __pyx_t_57 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":7680
 *             ccopy(&k_endog, &partial_autocorrelations[k,s*k_endog], &k_endog, &tmp[0, k], &inc)
 *         ctrtrs("L", "T", "N", &k_endog, &k_endog, &backward_factors[0,0], &k_endog,
 *                                                            &tmp[0, 0], &k_endog, &info)             # <<<<<<<<<<<<<<
 *         # cgemm("N", "T", &k_endog, &k_endog, &k_endog,
 *         #   &alpha, &forward_factors[0,0], &k_endog,
 */
    __pyx_t_58 = 0;
    __pyx_t_59 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":7679
 *         for k in range(k_endog):
 *             ccopy(&k_endog, &partial_autocorrelations[k,s*k_endog], &k_endog, &tmp[0, k], &inc)
 *         ctrtrs("L", "T", "N", &k_endog, &k_endog, &backward_factors[0,0], &k_endog,             # <<<<<<<<<<<<<<
 *                                                            &tmp[0, 0], &k_endog, &info)
 *         # cgemm("N", "T", &k_endog, &k_endog, &k_endog,
 */
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_ctrtrs(__pyx_k_L, __pyx_k_T, __pyx_k_N, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_backward_factors.data) + __pyx_t_56)) ) + __pyx_t_57 * __pyx_v_backward_factors.strides[1]) )))), (&__pyx_v_k_endog), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_tmp.data) + __pyx_t_58)) ) + __pyx_t_59 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_k_endog), (&__pyx_v_info));

    /* "statsmodels\tsa\statespace\_statespace.pyx":7686
 *         #   &beta, &forwards[s*k_endog2], &k_endog)
 *         ctrmm("R", "L", "T", "N", &k_endog, &k_endog,
 *           &alpha, &forward_factors[0,0], &k_endog,             # <<<<<<<<<<<<<<
 *                   &tmp[0, 0], &k_endog)
 *         for k in range(k_endog):
 */
    __pyx_t_60 = 0;
    __pyx_t_61 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":7687
 *         ctrmm("R", "L", "T", "N", &k_endog, &k_endog,
 *           &alpha, &forward_factors[0,0], &k_endog,
 *                   &tmp[0, 0], &k_endog)             # <<<<<<<<<<<<<<
 *         for k in range(k_endog):
 *             ccopy(&k_endog, &tmp[k,0], &k_endog, &forwards[s*k_endog2 + k*k_endog], &inc)
 */
    __pyx_t_62 = 0;
    __pyx_t_63 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":7685
 *         #           &tmp[0, 0], &k_endog,
 *         #   &beta, &forwards[s*k_endog2], &k_endog)
 *         ctrmm("R", "L", "T", "N", &k_endog, &k_endog,             # <<<<<<<<<<<<<<
 *           &alpha, &forward_factors[0,0], &k_endog,
 *                   &tmp[0, 0], &k_endog)
 */
    __pyx_v_ctrmm(__pyx_k_R, __pyx_k_L, __pyx_k_T, __pyx_k_N, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_alpha), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_forward_factors.data) + __pyx_t_60)) ) + __pyx_t_61 * __pyx_v_forward_factors.strides[1]) )))), (&__pyx_v_k_endog), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_tmp.data) + __pyx_t_62)) ) + __pyx_t_63 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_k_endog));

    /* "statsmodels\tsa\statespace\_statespace.pyx":7688
 *           &alpha, &forward_factors[0,0], &k_endog,
 *                   &tmp[0, 0], &k_endog)
 *         for k in range(k_endog):             # <<<<<<<<<<<<<<
 *             ccopy(&k_endog, &tmp[k,0], &k_endog, &forwards[s*k_endog2 + k*k_endog], &inc)
 * 
 */
    __pyx_t_50 = __pyx_v_k_endog;
    for (__pyx_t_51 = 0; __pyx_t_51 < __pyx_t_50; __pyx_t_51+=1) {
      __pyx_v_k = __pyx_t_51;

      /* "statsmodels\tsa\statespace\_statespace.pyx":7689
 *                   &tmp[0, 0], &k_endog)
 *         for k in range(k_endog):
 *             ccopy(&k_endog, &tmp[k,0], &k_endog, &forwards[s*k_endog2 + k*k_endog], &inc)             # <<<<<<<<<<<<<<
 * 
 *         # P' L^{-1} = x
 */
      __pyx_t_64 = __pyx_v_k;
      __pyx_t_65 = 0;
      __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_ccopy((&__pyx_v_k_endog), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_tmp.data) + __pyx_t_64)) ) + __pyx_t_65 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_k_endog), (&(__pyx_v_forwards[((__pyx_v_s * __pyx_v_k_endog2) + (__pyx_v_k * __pyx_v_k_endog))])), (&__pyx_v_inc));
    }

    /* "statsmodels\tsa\statespace\_statespace.pyx":7700
 *         #         lower=True, trans='T').T
 *         # )
 *         ccopy(&k_endog2, &partial_autocorrelations[0, s*k_endog], &inc, &tmp[0, 0], &inc)             # <<<<<<<<<<<<<<
 *         ctrtrs("L", "T", "N", &k_endog, &k_endog, &forward_factors[0, 0], &k_endog,
 *                                                            &tmp[0, 0], &k_endog, &info)
 */
    __pyx_t_66 = 0;
    __pyx_t_50 = (__pyx_v_s * __pyx_v_k_endog);
    __pyx_t_67 = 0;
    __pyx_t_68 = 0;
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_ccopy((&__pyx_v_k_endog2), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_partial_autocorrelations.data) + __pyx_t_66)) ) + __pyx_t_50 * __pyx_v_partial_autocorrelations.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_tmp.data) + __pyx_t_67)) ) + __pyx_t_68 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_inc));

    /* "statsmodels\tsa\statespace\_statespace.pyx":7701
 *         # )
 *         ccopy(&k_endog2, &partial_autocorrelations[0, s*k_endog], &inc, &tmp[0, 0], &inc)
 *         ctrtrs("L", "T", "N", &k_endog, &k_endog, &forward_factors[0, 0], &k_endog,             # <<<<<<<<<<<<<<
 *                                                            &tmp[0, 0], &k_endog, &info)
 *         # cgemm("N", "T", &k_endog, &k_endog, &k_endog,
 */
    __pyx_t_69 = 0;
    __pyx_t_70 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":7702
 *         ccopy(&k_endog2, &partial_autocorrelations[0, s*k_endog], &inc, &tmp[0, 0], &inc)
 *         ctrtrs("L", "T", "N", &k_endog, &k_endog, &forward_factors[0, 0], &k_endog,
 *                                                            &tmp[0, 0], &k_endog, &info)             # <<<<<<<<<<<<<<
 *         # cgemm("N", "T", &k_endog, &k_endog, &k_endog,
 *         #   &alpha, &backward_factors[0, 0], &k_endog,
 */
    __pyx_t_71 = 0;
    __pyx_t_72 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":7701
 *         # )
 *         ccopy(&k_endog2, &partial_autocorrelations[0, s*k_endog], &inc, &tmp[0, 0], &inc)
 *         ctrtrs("L", "T", "N", &k_endog, &k_endog, &forward_factors[0, 0], &k_endog,             # <<<<<<<<<<<<<<
 *                                                            &tmp[0, 0], &k_endog, &info)
 *         # cgemm("N", "T", &k_endog, &k_endog, &k_endog,
 */
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_ctrtrs(__pyx_k_L, __pyx_k_T, __pyx_k_N, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_forward_factors.data) + __pyx_t_69)) ) + __pyx_t_70 * __pyx_v_forward_factors.strides[1]) )))), (&__pyx_v_k_endog), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_tmp.data) + __pyx_t_71)) ) + __pyx_t_72 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_k_endog), (&__pyx_v_info));

    /* "statsmodels\tsa\statespace\_statespace.pyx":7708
 *         #   &beta, &backwards[s * k_endog2], &k_endog)
 *         ctrmm("R", "L", "T", "N", &k_endog, &k_endog,
 *           &alpha, &backward_factors[0,0], &k_endog,             # <<<<<<<<<<<<<<
 *                   &tmp[0, 0], &k_endog)
 *         for k in range(k_endog):
 */
    __pyx_t_73 = 0;
    __pyx_t_74 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":7709
 *         ctrmm("R", "L", "T", "N", &k_endog, &k_endog,
 *           &alpha, &backward_factors[0,0], &k_endog,
 *                   &tmp[0, 0], &k_endog)             # <<<<<<<<<<<<<<
 *         for k in range(k_endog):
 *             ccopy(&k_endog, &tmp[k,0], &k_endog, &backwards[s*k_endog2 + k*k_endog], &inc)
 */
    __pyx_t_75 = 0;
    __pyx_t_76 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":7707
 *         #           &tmp[0, 0], &k_endog,
 *         #   &beta, &backwards[s * k_endog2], &k_endog)
 *         ctrmm("R", "L", "T", "N", &k_endog, &k_endog,             # <<<<<<<<<<<<<<
 *           &alpha, &backward_factors[0,0], &k_endog,
 *                   &tmp[0, 0], &k_endog)
 */
    __pyx_v_ctrmm(__pyx_k_R, __pyx_k_L, __pyx_k_T, __pyx_k_N, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_alpha), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_backward_factors.data) + __pyx_t_73)) ) + __pyx_t_74 * __pyx_v_backward_factors.strides[1]) )))), (&__pyx_v_k_endog), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_tmp.data) + __pyx_t_75)) ) + __pyx_t_76 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_k_endog));

    /* "statsmodels\tsa\statespace\_statespace.pyx":7710
 *           &alpha, &backward_factors[0,0], &k_endog,
 *                   &tmp[0, 0], &k_endog)
 *         for k in range(k_endog):             # <<<<<<<<<<<<<<
 *             ccopy(&k_endog, &tmp[k,0], &k_endog, &backwards[s*k_endog2 + k*k_endog], &inc)
 * 
 */
    __pyx_t_51 = __pyx_v_k_endog;
    for (__pyx_t_77 = 0; __pyx_t_77 < __pyx_t_51; __pyx_t_77+=1) {
      __pyx_v_k = __pyx_t_77;

      /* "statsmodels\tsa\statespace\_statespace.pyx":7711
 *                   &tmp[0, 0], &k_endog)
 *         for k in range(k_endog):
 *             ccopy(&k_endog, &tmp[k,0], &k_endog, &backwards[s*k_endog2 + k*k_endog], &inc)             # <<<<<<<<<<<<<<
 * 
 *         # Update the variance
 */
      __pyx_t_78 = __pyx_v_k;
      __pyx_t_79 = 0;
      __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_ccopy((&__pyx_v_k_endog), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_tmp.data) + __pyx_t_78)) ) + __pyx_t_79 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_k_endog), (&(__pyx_v_backwards[((__pyx_v_s * __pyx_v_k_endog2) + (__pyx_v_k * __pyx_v_k_endog))])), (&__pyx_v_inc));
    }

    /* "statsmodels\tsa\statespace\_statespace.pyx":7720
 *         # tmpT = np.dot(backward_variance.T, forwards[:, s*k_endog:(s+1)*k_endog].T)
 *         cgemm("T", "T", &k_endog, &k_endog, &k_endog,
 *           &alpha, &backward_variance[0, 0], &k_endog,             # <<<<<<<<<<<<<<
 *                   &forwards[s * k_endog2], &k_endog,
 *           &beta, &tmp[0, 0], &k_endog)
 */
    __pyx_t_80 = 0;
    __pyx_t_81 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":7722
 *           &alpha, &backward_variance[0, 0], &k_endog,
 *                   &forwards[s * k_endog2], &k_endog,
 *           &beta, &tmp[0, 0], &k_endog)             # <<<<<<<<<<<<<<
 *         # autocovariances[:, (s+1)*k_endog:(s+2)*k_endog] = tmp.copy().T
 *         ccopy(&k_endog2, &tmp[0, 0], &inc, &autocovariances[0, (s+1)*k_endog], &inc)
 */
    __pyx_t_82 = 0;
    __pyx_t_83 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":7719
 *         # tmp = np.dot(forwards[:, s*k_endog:(s+1)*k_endog], backward_variance)
 *         # tmpT = np.dot(backward_variance.T, forwards[:, s*k_endog:(s+1)*k_endog].T)
 *         cgemm("T", "T", &k_endog, &k_endog, &k_endog,             # <<<<<<<<<<<<<<
 *           &alpha, &backward_variance[0, 0], &k_endog,
 *                   &forwards[s * k_endog2], &k_endog,
 */
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_cgemm(__pyx_k_T, __pyx_k_T, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_alpha), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_backward_variance.data) + __pyx_t_80)) ) + __pyx_t_81 * __pyx_v_backward_variance.strides[1]) )))), (&__pyx_v_k_endog), (&(__pyx_v_forwards[(__pyx_v_s * __pyx_v_k_endog2)])), (&__pyx_v_k_endog), (&__pyx_v_beta), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_tmp.data) + __pyx_t_82)) ) + __pyx_t_83 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_k_endog));

    /* "statsmodels\tsa\statespace\_statespace.pyx":7724
 *           &beta, &tmp[0, 0], &k_endog)
 *         # autocovariances[:, (s+1)*k_endog:(s+2)*k_endog] = tmp.copy().T
 *         ccopy(&k_endog2, &tmp[0, 0], &inc, &autocovariances[0, (s+1)*k_endog], &inc)             # <<<<<<<<<<<<<<
 * 
 *         # Create the remaining k = 1, ..., s matrices,
 */
    __pyx_t_84 = 0;
    __pyx_t_85 = 0;
    __pyx_t_86 = 0;
    __pyx_t_87 = ((__pyx_v_s + 1) * __pyx_v_k_endog);
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_ccopy((&__pyx_v_k_endog2), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_tmp.data) + __pyx_t_84)) ) + __pyx_t_85 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_autocovariances.data) + __pyx_t_86)) ) + __pyx_t_87 * __pyx_v_autocovariances.strides[1]) )))), (&__pyx_v_inc));

    /* "statsmodels\tsa\statespace\_statespace.pyx":7728
 *         # Create the remaining k = 1, ..., s matrices,
 *         # only has an effect if s >= 1
 *         for k in range(s):             # <<<<<<<<<<<<<<
 *             # forwards[:, k*k_endog:(k+1)*k_endog] = (
 *             #     prev_forwards[:, k*k_endog:(k+1)*k_endog] -
 */
    __pyx_t_51 = __pyx_v_s;
    for (__pyx_t_77 = 0; __pyx_t_77 < __pyx_t_51; __pyx_t_77+=1) {
      __pyx_v_k = __pyx_t_77;

      /* "statsmodels\tsa\statespace\_statespace.pyx":7736
 *             #     )
 *             # )
 *             ccopy(&k_endog2, &prev_forwards[k * k_endog2], &inc, &forwards[k * k_endog2], &inc)             # <<<<<<<<<<<<<<
 *             cgemm("N", "N", &k_endog, &k_endog, &k_endog,
 *               &gamma, &forwards[s * k_endog2], &k_endog,
 */
      __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_ccopy((&__pyx_v_k_endog2), (&(__pyx_v_prev_forwards[(__pyx_v_k * __pyx_v_k_endog2)])), (&__pyx_v_inc), (&(__pyx_v_forwards[(__pyx_v_k * __pyx_v_k_endog2)])), (&__pyx_v_inc));

      /* "statsmodels\tsa\statespace\_statespace.pyx":7737
 *             # )
 *             ccopy(&k_endog2, &prev_forwards[k * k_endog2], &inc, &forwards[k * k_endog2], &inc)
 *             cgemm("N", "N", &k_endog, &k_endog, &k_endog,             # <<<<<<<<<<<<<<
 *               &gamma, &forwards[s * k_endog2], &k_endog,
 *                       &prev_backwards[(s - k - 1) * k_endog2], &k_endog,
 */
      __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_cgemm(__pyx_k_N, __pyx_k_N, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_gamma), (&(__pyx_v_forwards[(__pyx_v_s * __pyx_v_k_endog2)])), (&__pyx_v_k_endog), (&(__pyx_v_prev_backwards[(((__pyx_v_s - __pyx_v_k) - 1) * __pyx_v_k_endog2)])), (&__pyx_v_k_endog), (&__pyx_v_alpha), (&(__pyx_v_forwards[(__pyx_v_k * __pyx_v_k_endog2)])), (&__pyx_v_k_endog));

      /* "statsmodels\tsa\statespace\_statespace.pyx":7749
 *             #     )
 *             # )
 *             ccopy(&k_endog2, &prev_backwards[k * k_endog2], &inc, &backwards[k * k_endog2], &inc)             # <<<<<<<<<<<<<<
 *             cgemm("N", "N", &k_endog, &k_endog, &k_endog,
 *               &gamma, &backwards[s * k_endog2], &k_endog,
 */
      __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_ccopy((&__pyx_v_k_endog2), (&(__pyx_v_prev_backwards[(__pyx_v_k * __pyx_v_k_endog2)])), (&__pyx_v_inc), (&(__pyx_v_backwards[(__pyx_v_k * __pyx_v_k_endog2)])), (&__pyx_v_inc));

      /* "statsmodels\tsa\statespace\_statespace.pyx":7750
 *             # )
 *             ccopy(&k_endog2, &prev_backwards[k * k_endog2], &inc, &backwards[k * k_endog2], &inc)
 *             cgemm("N", "N", &k_endog, &k_endog, &k_endog,             # <<<<<<<<<<<<<<
 *               &gamma, &backwards[s * k_endog2], &k_endog,
 *                       &prev_forwards[(s - k - 1) * k_endog2], &k_endog,
 */
      __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_cgemm(__pyx_k_N, __pyx_k_N, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_gamma), (&(__pyx_v_backwards[(__pyx_v_s * __pyx_v_k_endog2)])), (&__pyx_v_k_endog), (&(__pyx_v_prev_forwards[(((__pyx_v_s - __pyx_v_k) - 1) * __pyx_v_k_endog2)])), (&__pyx_v_k_endog), (&__pyx_v_alpha), (&(__pyx_v_backwards[(__pyx_v_k * __pyx_v_k_endog2)])), (&__pyx_v_k_endog));

      /* "statsmodels\tsa\statespace\_statespace.pyx":7760
 *             # )
 *             cgemm("N", "T", &k_endog, &k_endog, &k_endog,
 *               &alpha, &autocovariances[0, (k+1)*k_endog], &k_endog,             # <<<<<<<<<<<<<<
 *                       &prev_forwards[(s - k - 1) * k_endog2], &k_endog,
 *               &alpha, &autocovariances[0, (s+1)*k_endog], &k_endog)
 */
      __pyx_t_88 = 0;
      __pyx_t_89 = ((__pyx_v_k + 1) * __pyx_v_k_endog);

      /* "statsmodels\tsa\statespace\_statespace.pyx":7762
 *               &alpha, &autocovariances[0, (k+1)*k_endog], &k_endog,
 *                       &prev_forwards[(s - k - 1) * k_endog2], &k_endog,
 *               &alpha, &autocovariances[0, (s+1)*k_endog], &k_endog)             # <<<<<<<<<<<<<<
 * 
 *         # Create forward and backwards variances
 */
      __pyx_t_90 = 0;
      __pyx_t_91 = ((__pyx_v_s + 1) * __pyx_v_k_endog);

      /* "statsmodels\tsa\statespace\_statespace.pyx":7759
 *             #     prev_forwards[:, (s-k-1)*k_endog:(s-k)*k_endog].T
 *             # )
 *             cgemm("N", "T", &k_endog, &k_endog, &k_endog,             # <<<<<<<<<<<<<<
 *               &alpha, &autocovariances[0, (k+1)*k_endog], &k_endog,
 *                       &prev_forwards[(s - k - 1) * k_endog2], &k_endog,
 */
      __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_cgemm(__pyx_k_N, __pyx_k_T, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_alpha), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_autocovariances.data) + __pyx_t_88)) ) + __pyx_t_89 * __pyx_v_autocovariances.strides[1]) )))), (&__pyx_v_k_endog), (&(__pyx_v_prev_forwards[(((__pyx_v_s - __pyx_v_k) - 1) * __pyx_v_k_endog2)])), (&__pyx_v_k_endog), (&__pyx_v_alpha), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_autocovariances.data) + __pyx_t_90)) ) + __pyx_t_91 * __pyx_v_autocovariances.strides[1]) )))), (&__pyx_v_k_endog));
    }

    /* "statsmodels\tsa\statespace\_statespace.pyx":7774
 *         cgemm("N", "N", &k_endog, &k_endog, &k_endog,
 *           &alpha, &backwards[s * k_endog2], &k_endog,
 *                   &forward_variance[0, 0], &k_endog,             # <<<<<<<<<<<<<<
 *           &beta, &tmp2[0, 0], &k_endog)
 *         cgemm("N", "T", &k_endog, &k_endog, &k_endog,
 */
    __pyx_t_92 = 0;
    __pyx_t_93 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":7775
 *           &alpha, &backwards[s * k_endog2], &k_endog,
 *                   &forward_variance[0, 0], &k_endog,
 *           &beta, &tmp2[0, 0], &k_endog)             # <<<<<<<<<<<<<<
 *         cgemm("N", "T", &k_endog, &k_endog, &k_endog,
 *           &gamma, &tmp2[0, 0], &k_endog,
 */
    __pyx_t_94 = 0;
    __pyx_t_95 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":7772
 *         #     )
 *         # )
 *         cgemm("N", "N", &k_endog, &k_endog, &k_endog,             # <<<<<<<<<<<<<<
 *           &alpha, &backwards[s * k_endog2], &k_endog,
 *                   &forward_variance[0, 0], &k_endog,
 */
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_cgemm(__pyx_k_N, __pyx_k_N, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_alpha), (&(__pyx_v_backwards[(__pyx_v_s * __pyx_v_k_endog2)])), (&__pyx_v_k_endog), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_forward_variance.data) + __pyx_t_92)) ) + __pyx_t_93 * __pyx_v_forward_variance.strides[1]) )))), (&__pyx_v_k_endog), (&__pyx_v_beta), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_tmp2.data) + __pyx_t_94)) ) + __pyx_t_95 * __pyx_v_tmp2.strides[1]) )))), (&__pyx_v_k_endog));

    /* "statsmodels\tsa\statespace\_statespace.pyx":7777
 *           &beta, &tmp2[0, 0], &k_endog)
 *         cgemm("N", "T", &k_endog, &k_endog, &k_endog,
 *           &gamma, &tmp2[0, 0], &k_endog,             # <<<<<<<<<<<<<<
 *                   &backwards[s * k_endog2], &k_endog,
 *           &alpha, &backward_variance[0, 0], &k_endog)
 */
    __pyx_t_96 = 0;
    __pyx_t_97 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":7779
 *           &gamma, &tmp2[0, 0], &k_endog,
 *                   &backwards[s * k_endog2], &k_endog,
 *           &alpha, &backward_variance[0, 0], &k_endog)             # <<<<<<<<<<<<<<
 *         # forward_variance = (
 *         #     forward_variance -
 */
    __pyx_t_98 = 0;
    __pyx_t_99 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":7776
 *                   &forward_variance[0, 0], &k_endog,
 *           &beta, &tmp2[0, 0], &k_endog)
 *         cgemm("N", "T", &k_endog, &k_endog, &k_endog,             # <<<<<<<<<<<<<<
 *           &gamma, &tmp2[0, 0], &k_endog,
 *                   &backwards[s * k_endog2], &k_endog,
 */
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_cgemm(__pyx_k_N, __pyx_k_T, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_gamma), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_tmp2.data) + __pyx_t_96)) ) + __pyx_t_97 * __pyx_v_tmp2.strides[1]) )))), (&__pyx_v_k_endog), (&(__pyx_v_backwards[(__pyx_v_s * __pyx_v_k_endog2)])), (&__pyx_v_k_endog), (&__pyx_v_alpha), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_backward_variance.data) + __pyx_t_98)) ) + __pyx_t_99 * __pyx_v_backward_variance.strides[1]) )))), (&__pyx_v_k_endog));

    /* "statsmodels\tsa\statespace\_statespace.pyx":7789
 *         # )
 *         cgemm("T", "T", &k_endog, &k_endog, &k_endog,
 *           &gamma, &tmp[0, 0], &k_endog,             # <<<<<<<<<<<<<<
 *                   &forwards[s * k_endog2], &k_endog,
 *           &alpha, &forward_variance[0, 0], &k_endog)
 */
    __pyx_t_100 = 0;
    __pyx_t_101 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":7791
 *           &gamma, &tmp[0, 0], &k_endog,
 *                   &forwards[s * k_endog2], &k_endog,
 *           &alpha, &forward_variance[0, 0], &k_endog)             # <<<<<<<<<<<<<<
 * 
 *         # Cholesky factors
 */
    __pyx_t_102 = 0;
    __pyx_t_103 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":7788
 *         #     np.dot(tmpT.T, forwards[:, s*k_endog:(s+1)*k_endog].T)
 *         # )
 *         cgemm("T", "T", &k_endog, &k_endog, &k_endog,             # <<<<<<<<<<<<<<
 *           &gamma, &tmp[0, 0], &k_endog,
 *                   &forwards[s * k_endog2], &k_endog,
 */
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_cgemm(__pyx_k_T, __pyx_k_T, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&__pyx_v_gamma), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_tmp.data) + __pyx_t_100)) ) + __pyx_t_101 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_k_endog), (&(__pyx_v_forwards[(__pyx_v_s * __pyx_v_k_endog2)])), (&__pyx_v_k_endog), (&__pyx_v_alpha), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_forward_variance.data) + __pyx_t_102)) ) + __pyx_t_103 * __pyx_v_forward_variance.strides[1]) )))), (&__pyx_v_k_endog));

    /* "statsmodels\tsa\statespace\_statespace.pyx":7796
 *         # forward_factors = linalg.cholesky(forward_variance, lower=True)
 *         # backward_factors =  linalg.cholesky(backward_variance, lower=True)
 *         ccopy(&k_endog2, &forward_variance[0,0], &inc, &forward_factors[0,0], &inc)             # <<<<<<<<<<<<<<
 *         cpotrf("L", &k_endog, &forward_factors[0,0], &k_endog, &info)
 *         ccopy(&k_endog2, &backward_variance[0,0], &inc, &backward_factors[0,0], &inc)
 */
    __pyx_t_104 = 0;
    __pyx_t_105 = 0;
    __pyx_t_106 = 0;
    __pyx_t_107 = 0;
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_ccopy((&__pyx_v_k_endog2), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_forward_variance.data) + __pyx_t_104)) ) + __pyx_t_105 * __pyx_v_forward_variance.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_forward_factors.data) + __pyx_t_106)) ) + __pyx_t_107 * __pyx_v_forward_factors.strides[1]) )))), (&__pyx_v_inc));

    /* "statsmodels\tsa\statespace\_statespace.pyx":7797
 *         # backward_factors =  linalg.cholesky(backward_variance, lower=True)
 *         ccopy(&k_endog2, &forward_variance[0,0], &inc, &forward_factors[0,0], &inc)
 *         cpotrf("L", &k_endog, &forward_factors[0,0], &k_endog, &info)             # <<<<<<<<<<<<<<
 *         ccopy(&k_endog2, &backward_variance[0,0], &inc, &backward_factors[0,0], &inc)
 *         cpotrf("L", &k_endog, &backward_factors[0,0], &k_endog, &info)
 */
    __pyx_t_108 = 0;
    __pyx_t_109 = 0;
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_cpotrf(__pyx_k_L, (&__pyx_v_k_endog), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_forward_factors.data) + __pyx_t_108)) ) + __pyx_t_109 * __pyx_v_forward_factors.strides[1]) )))), (&__pyx_v_k_endog), (&__pyx_v_info));

    /* "statsmodels\tsa\statespace\_statespace.pyx":7798
 *         ccopy(&k_endog2, &forward_variance[0,0], &inc, &forward_factors[0,0], &inc)
 *         cpotrf("L", &k_endog, &forward_factors[0,0], &k_endog, &info)
 *         ccopy(&k_endog2, &backward_variance[0,0], &inc, &backward_factors[0,0], &inc)             # <<<<<<<<<<<<<<
 *         cpotrf("L", &k_endog, &backward_factors[0,0], &k_endog, &info)
 * 
 */
    __pyx_t_110 = 0;
    __pyx_t_111 = 0;
    __pyx_t_112 = 0;
    __pyx_t_113 = 0;
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_ccopy((&__pyx_v_k_endog2), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_backward_variance.data) + __pyx_t_110)) ) + __pyx_t_111 * __pyx_v_backward_variance.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_backward_factors.data) + __pyx_t_112)) ) + __pyx_t_113 * __pyx_v_backward_factors.strides[1]) )))), (&__pyx_v_inc));

    /* "statsmodels\tsa\statespace\_statespace.pyx":7799
 *         cpotrf("L", &k_endog, &forward_factors[0,0], &k_endog, &info)
 *         ccopy(&k_endog2, &backward_variance[0,0], &inc, &backward_factors[0,0], &inc)
 *         cpotrf("L", &k_endog, &backward_factors[0,0], &k_endog, &info)             # <<<<<<<<<<<<<<
 * 
 * 
 */
    __pyx_t_114 = 0;
    __pyx_t_115 = 0;
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_cpotrf(__pyx_k_L, (&__pyx_v_k_endog), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_backward_factors.data) + __pyx_t_114)) ) + __pyx_t_115 * __pyx_v_backward_factors.strides[1]) )))), (&__pyx_v_k_endog), (&__pyx_v_info));
  }

  /* "statsmodels\tsa\statespace\_statespace.pyx":7804
 *     # If we do not want to use the transformed variance, we need to
 *     # adjust the constrained matrices, as presented in Lemma 2.3, see above
 *     if not transform_variance:             # <<<<<<<<<<<<<<
 *         if order % 2 == 0:
 *             forwards = &forwards2[0,0]
 */
  __pyx_t_3 = ((!(__pyx_v_transform_variance != 0)) != 0);
  if (__pyx_t_3) {

    /* "statsmodels\tsa\statespace\_statespace.pyx":7805
 *     # adjust the constrained matrices, as presented in Lemma 2.3, see above
 *     if not transform_variance:
 *         if order % 2 == 0:             # <<<<<<<<<<<<<<
 *             forwards = &forwards2[0,0]
 *         else:
 */
    __pyx_t_3 = ((__Pyx_mod_long(__pyx_v_order, 2) == 0) != 0);
    if (__pyx_t_3) {

      /* "statsmodels\tsa\statespace\_statespace.pyx":7806
 *     if not transform_variance:
 *         if order % 2 == 0:
 *             forwards = &forwards2[0,0]             # <<<<<<<<<<<<<<
 *         else:
 *             forwards = &forwards1[0,0]
 */
      __pyx_t_116 = 0;
      __pyx_t_117 = 0;
      __pyx_v_forwards = (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_forwards2.data) + __pyx_t_116)) ) + __pyx_t_117 * __pyx_v_forwards2.strides[1]) ))));
      goto __pyx_L16;
    }
    /*else*/ {

      /* "statsmodels\tsa\statespace\_statespace.pyx":7808
 *             forwards = &forwards2[0,0]
 *         else:
 *             forwards = &forwards1[0,0]             # <<<<<<<<<<<<<<
 * 
 *         # Here, we need to construct T such that:
 */
      __pyx_t_118 = 0;
      __pyx_t_119 = 0;
      __pyx_v_forwards = (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_forwards1.data) + __pyx_t_118)) ) + __pyx_t_119 * __pyx_v_forwards1.strides[1]) ))));
    }
    __pyx_L16:;

    /* "statsmodels\tsa\statespace\_statespace.pyx":7819
 *         # initial_variance_factor = np.linalg.cholesky(initial_variance)
 *         # L'
 *         cpotrf("U", &k_endog, &initial_variance[0,0], &k_endog, &info)             # <<<<<<<<<<<<<<
 *         # transformed_variance_factor = np.linalg.cholesky(variance)
 *         # M'
 */
    if (unlikely(!__pyx_v_initial_variance.memview)) { __Pyx_RaiseUnboundLocalError("initial_variance"); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 7819; __pyx_clineno = __LINE__; goto __pyx_L1_error;} }
    __pyx_t_120 = 0;
    __pyx_t_121 = 0;
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_cpotrf(__pyx_k_U, (&__pyx_v_k_endog), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_initial_variance.data) + __pyx_t_120)) ) + __pyx_t_121 * __pyx_v_initial_variance.strides[1]) )))), (&__pyx_v_k_endog), (&__pyx_v_info));

    /* "statsmodels\tsa\statespace\_statespace.pyx":7822
 *         # transformed_variance_factor = np.linalg.cholesky(variance)
 *         # M'
 *         ccopy(&k_endog2, &forward_variance[0,0], &inc, &tmp[0,0], &inc)             # <<<<<<<<<<<<<<
 *         cpotrf("U", &k_endog, &tmp[0,0], &k_endog, &info)
 *         # cpotri("L", &k_endog, &tmp[0,0], &k_endog, &info)
 */
    __pyx_t_122 = 0;
    __pyx_t_123 = 0;
    __pyx_t_124 = 0;
    __pyx_t_125 = 0;
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_ccopy((&__pyx_v_k_endog2), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_forward_variance.data) + __pyx_t_122)) ) + __pyx_t_123 * __pyx_v_forward_variance.strides[1]) )))), (&__pyx_v_inc), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_tmp.data) + __pyx_t_124)) ) + __pyx_t_125 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_inc));

    /* "statsmodels\tsa\statespace\_statespace.pyx":7823
 *         # M'
 *         ccopy(&k_endog2, &forward_variance[0,0], &inc, &tmp[0,0], &inc)
 *         cpotrf("U", &k_endog, &tmp[0,0], &k_endog, &info)             # <<<<<<<<<<<<<<
 *         # cpotri("L", &k_endog, &tmp[0,0], &k_endog, &info)
 * 
 */
    __pyx_t_126 = 0;
    __pyx_t_127 = 0;
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_cpotrf(__pyx_k_U, (&__pyx_v_k_endog), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_tmp.data) + __pyx_t_126)) ) + __pyx_t_127 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_k_endog), (&__pyx_v_info));

    /* "statsmodels\tsa\statespace\_statespace.pyx":7828
 *         # We need to zero out the lower triangle of L', because ?trtrs only
 *         # knows that M' is upper triangular
 *         for s in range(k_endog - 1):          # column             # <<<<<<<<<<<<<<
 *             for k in range(s+1, k_endog):     # row
 *                 initial_variance[k, s] = 0
 */
    __pyx_t_128 = (__pyx_v_k_endog - 1);
    for (__pyx_t_32 = 0; __pyx_t_32 < __pyx_t_128; __pyx_t_32+=1) {
      __pyx_v_s = __pyx_t_32;

      /* "statsmodels\tsa\statespace\_statespace.pyx":7829
 *         # knows that M' is upper triangular
 *         for s in range(k_endog - 1):          # column
 *             for k in range(s+1, k_endog):     # row             # <<<<<<<<<<<<<<
 *                 initial_variance[k, s] = 0
 * 
 */
      __pyx_t_33 = __pyx_v_k_endog;
      for (__pyx_t_51 = (__pyx_v_s + 1); __pyx_t_51 < __pyx_t_33; __pyx_t_51+=1) {
        __pyx_v_k = __pyx_t_51;

        /* "statsmodels\tsa\statespace\_statespace.pyx":7830
 *         for s in range(k_endog - 1):          # column
 *             for k in range(s+1, k_endog):     # row
 *                 initial_variance[k, s] = 0             # <<<<<<<<<<<<<<
 * 
 *         # Note that T is lower triangular
 */
        if (unlikely(!__pyx_v_initial_variance.memview)) { __Pyx_RaiseUnboundLocalError("initial_variance"); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 7830; __pyx_clineno = __LINE__; goto __pyx_L1_error;} }
        __pyx_t_77 = __pyx_v_k;
        __pyx_t_129 = __pyx_v_s;
        *((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_initial_variance.data) + __pyx_t_77)) ) + __pyx_t_129 * __pyx_v_initial_variance.strides[1]) )) = __pyx_t_float_complex_from_parts(0, 0);
      }
    }

    /* "statsmodels\tsa\statespace\_statespace.pyx":7837
 *         # transform = np.dot(initial_variance_factor,
 *         #                    np.linalg.inv(transformed_variance_factor))
 *         ctrtrs("U", "N", "N", &k_endog, &k_endog, &tmp[0,0], &k_endog,             # <<<<<<<<<<<<<<
 *                                                            &initial_variance[0, 0], &k_endog, &info)
 *         # Now:
 */
    __pyx_t_130 = 0;
    __pyx_t_131 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":7838
 *         #                    np.linalg.inv(transformed_variance_factor))
 *         ctrtrs("U", "N", "N", &k_endog, &k_endog, &tmp[0,0], &k_endog,
 *                                                            &initial_variance[0, 0], &k_endog, &info)             # <<<<<<<<<<<<<<
 *         # Now:
 *         # initial_variance = T'
 */
    if (unlikely(!__pyx_v_initial_variance.memview)) { __Pyx_RaiseUnboundLocalError("initial_variance"); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 7838; __pyx_clineno = __LINE__; goto __pyx_L1_error;} }
    __pyx_t_132 = 0;
    __pyx_t_133 = 0;

    /* "statsmodels\tsa\statespace\_statespace.pyx":7837
 *         # transform = np.dot(initial_variance_factor,
 *         #                    np.linalg.inv(transformed_variance_factor))
 *         ctrtrs("U", "N", "N", &k_endog, &k_endog, &tmp[0,0], &k_endog,             # <<<<<<<<<<<<<<
 *                                                            &initial_variance[0, 0], &k_endog, &info)
 *         # Now:
 */
    __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_ctrtrs(__pyx_k_U, __pyx_k_N, __pyx_k_N, (&__pyx_v_k_endog), (&__pyx_v_k_endog), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_tmp.data) + __pyx_t_130)) ) + __pyx_t_131 * __pyx_v_tmp.strides[1]) )))), (&__pyx_v_k_endog), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_initial_variance.data) + __pyx_t_132)) ) + __pyx_t_133 * __pyx_v_initial_variance.strides[1]) )))), (&__pyx_v_k_endog), (&__pyx_v_info));

    /* "statsmodels\tsa\statespace\_statespace.pyx":7842
 *         # initial_variance = T'
 * 
 *         for s in range(order):             # <<<<<<<<<<<<<<
 *             # forwards[:, s*k_endog:(s+1)*k_endog] = (
 *             #     np.dot(
 */
    __pyx_t_32 = __pyx_v_order;
    for (__pyx_t_33 = 0; __pyx_t_33 < __pyx_t_32; __pyx_t_33+=1) {
      __pyx_v_s = __pyx_t_33;

      /* "statsmodels\tsa\statespace\_statespace.pyx":7854
 * 
 *             # Get TF
 *             ccopy(&k_endog2, &forwards[s * k_endog2], &inc, &tmp2[0,0], &inc)             # <<<<<<<<<<<<<<
 *             ctrmm("L", "U", "T", "N", &k_endog, &k_endog,
 *               &alpha, &initial_variance[0, 0], &k_endog,
 */
      __pyx_t_134 = 0;
      __pyx_t_135 = 0;
      __pyx_v_11statsmodels_3tsa_10statespace_11_statespace_ccopy((&__pyx_v_k_endog2), (&(__pyx_v_forwards[(__pyx_v_s * __pyx_v_k_endog2)])), (&__pyx_v_inc), (&(*((__pyx_t_float_complex *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((__pyx_t_float_complex *) __pyx_v_tmp2.data) + __pyx_t_134)) ) + __pyx_t_135 * __pyx_v_tmp2.strides[1]) )))), (&__pyx_v_inc));

      /* "statsmodels\tsa\statespace\_statespace.pyx":7856
 *             ccopy(&k_endog2, &forwards[s * k_endog2], &inc, &tmp2[0,0], &inc)
 *             ctrmm("L", "U", "T", "N", &k_endog, &k_endog,
 *               &alpha, &initial_variance[0, 0], &k_endog,             # <<<<<<<<<<<<<<
 *                       &tmp2[0, 0], &k_endog)
 *             for k in range(k_endog):
 */
      if (unlikely(!__pyx_v_initial_variance.memview)) { __Pyx_RaiseUnboundLocalError("initial_variance"); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 7856; __pyx_clineno = __LINE__; goto __pyx_L1_error;} }
      __pyx_t_136 = 0;
      __pyx_t_137 = 0;

      /* "statsmodels\tsa\statespace\_statespace.pyx":7857
 *             ctrmm("L", "U", "T", "N", &k_endog, &k_endog,
 *               &alpha, &initial_variance[0, 0], &k_endog,
 *                       &tmp2[0, 0], &k_endog)             # <<<<<<<<<<<<<<
 *             for k in range(k_endog):
 *                 ccopy(&k_endog, &tmp2[k,0], &k_endog, &tmp[0, k], &inc)
 */
      __pyx_t_138 = 0;
      __pyx_t_139 = 0;

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    /* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":222
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  /* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":224
 *                 raise ValueError(u"ndarray is not Fortran contiguous")
 * 
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 */
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  /* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":225
 * 
 *             info.buf = PyArray_DATA(self)
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 *             if copy_shape:
 *                 # Allocate new buffer for strides and shape info.
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  /* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":226
 *             info.buf = PyArray_DATA(self)
 *             info.ndim = ndim
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    /* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":229
 *                 # Allocate new buffer for strides and shape info.
 *                 # This is allocated as one block, strides first.
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 *                 info.shape = info.strides + ndim
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 */
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    /* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":230
 *                 # This is allocated as one block, strides first.
 *                 info.strides = <Py_ssize_t*>stdlib.malloc(sizeof(Py_ssize_t) * <size_t>ndim * 2)
 *                 info.shape = info.strides + ndim             # <<<<<<<<<<<<<<
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    /* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":231
 *                 info.strides = <Py_ssize_t*>stdlib.malloc(sizeof(Py_ssize_t) * <size_t>ndim * 2)
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 *                 for i in range(ndim):             # <<<<<<<<<<<<<<
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      /* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":232
 *                 info.shape = info.strides + ndim
 *                 for i in range(ndim):
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 */
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      /* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":233
 *                 for i in range(ndim):
 *                     info.strides[i] = PyArray_STRIDES(self)[i]
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    /* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":235
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 *             else:
 *                 info.strides = <Py_ssize_t*>PyArray_STRIDES(self)             # <<<<<<<<<<<<<<
 *                 info.shape = <Py_ssize_t*>PyArray_DIMS(self)
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    /* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":236
 *             else:
 *                 info.strides = <Py_ssize_t*>PyArray_STRIDES(self)
 *                 info.shape = <Py_ssize_t*>PyArray_DIMS(self)             # <<<<<<<<<<<<<<
 *             info.suboffsets = NULL
 *             info.itemsize = PyArray_ITEMSIZE(self)
 */
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  /* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":237
 *                 info.strides = <Py_ssize_t*>PyArray_STRIDES(self)
 *                 info.shape = <Py_ssize_t*>PyArray_DIMS(self)
 *             info.suboffsets = NULL             # <<<<<<<<<<<<<<
 *             info.itemsize = PyArray_ITEMSIZE(self)
 *             info.readonly = not PyArray_ISWRITEABLE(self)
 */
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  /* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":238
 *                 info.shape = <Py_ssize_t*>PyArray_DIMS(self)
 *             info.suboffsets = NULL
 *             info.itemsize = PyArray_ITEMSIZE(self)             # <<<<<<<<<<<<<<
 *             info.readonly = not PyArray_ISWRITEABLE(self)
 * 
 */
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  /* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":239
 *             info.suboffsets = NULL
 *             info.itemsize = PyArray_ITEMSIZE(self)
 *             info.readonly = not PyArray_ISWRITEABLE(self)             # <<<<<<<<<<<<<<
 * 
 *             cdef int t
 */
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  /* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":242
 * 
 *             cdef int t
 *             cdef char* f = NULL             # <<<<<<<<<<<<<<
 *             cdef dtype descr = self.descr
 *             cdef list stack
 */
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  /* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":243
 *             cdef int t
 *             cdef char* f = NULL
 *             cdef dtype descr = self.descr             # <<<<<<<<<<<<<<
 *             cdef list stack
 *             cdef int offset
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  /* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":247
 *             cdef int offset
 * 
 *             cdef bint hasfields = PyDataType_HASFIELDS(descr)             # <<<<<<<<<<<<<<
 * 
 *             if not hasfields and not copy_shape:
 */
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  /* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":249
 *             cdef bint hasfields = PyDataType_HASFIELDS(descr)
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 *             if not hasfields and not copy_shape:             # <<<<<<<<<<<<<<
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  __pyx_L15_bool_binop_done:;
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    /* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":251
 *             if not hasfields and not copy_shape:
 *                 # do not call releasebuffer
 *                 info.obj = None             # <<<<<<<<<<<<<<
 *             else:
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 */
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    __Pyx_GIVEREF(Py_None);
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    __pyx_v_info->obj = Py_None;
    goto __pyx_L14;
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  /*else*/ {

    /* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":254
 *             else:
 *                 # need to call releasebuffer
 *                 info.obj = self             # <<<<<<<<<<<<<<
 * 
 *             if not hasfields:
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    __Pyx_INCREF(((PyObject *)__pyx_v_self));
    __Pyx_GIVEREF(((PyObject *)__pyx_v_self));
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  __pyx_L14:;

  /* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":256
 *                 info.obj = self
 * 
 *             if not hasfields:             # <<<<<<<<<<<<<<
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    /* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":257
 * 
 *             if not hasfields:
 *                 t = descr.type_num             # <<<<<<<<<<<<<<
 *                 if ((descr.byteorder == c'>' and little_endian) or
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    /* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":258
 *             if not hasfields:
 *                 t = descr.type_num
 *                 if ((descr.byteorder == c'>' and little_endian) or             # <<<<<<<<<<<<<<
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 */
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    /* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":259
 *                 t = descr.type_num
 *                 if ((descr.byteorder == c'>' and little_endian) or
 *                     (descr.byteorder == c'<' and not little_endian)):             # <<<<<<<<<<<<<<
 *                     raise ValueError(u"Non-native byte order not supported")
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      __pyx_t_1 = __pyx_t_2;
      goto __pyx_L19_bool_binop_done;
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    __pyx_t_2 = ((!(__pyx_v_little_endian != 0)) != 0);
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      /* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":260
 *                 if ((descr.byteorder == c'>' and little_endian) or
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 *                     raise ValueError(u"Non-native byte order not supported")             # <<<<<<<<<<<<<<
 *                 if   t == NPY_BYTE:        f = "b"
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      __pyx_t_3 = __Pyx_PyObject_Call(__pyx_builtin_ValueError, __pyx_tuple__39, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 260; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
      __Pyx_GOTREF(__pyx_t_3);
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    /* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":277
 *                 elif t == NPY_CDOUBLE:     f = "Zd"
 *                 elif t == NPY_CLONGDOUBLE: f = "Zg"
 *                 elif t == NPY_OBJECT:      f = "O"             # <<<<<<<<<<<<<<
 *                 else:
 *                     raise ValueError(u"unknown dtype code in numpy.pxd (%d)" % t)
 */
    switch (__pyx_v_t) {

      /* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":261
 *                     (descr.byteorder == c'<' and not little_endian)):
 *                     raise ValueError(u"Non-native byte order not supported")
 *                 if   t == NPY_BYTE:        f = "b"             # <<<<<<<<<<<<<<
 *                 elif t == NPY_UBYTE:       f = "B"
 *                 elif t == NPY_SHORT:       f = "h"
 */
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      __pyx_v_f = __pyx_k_b;
      break;

      /* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":262
 *                     raise ValueError(u"Non-native byte order not supported")
 *                 if   t == NPY_BYTE:        f = "b"
 *                 elif t == NPY_UBYTE:       f = "B"             # <<<<<<<<<<<<<<
 *                 elif t == NPY_SHORT:       f = "h"
 *                 elif t == NPY_USHORT:      f = "H"
 */
      case NPY_UBYTE:
      __pyx_v_f = __pyx_k_B;
      break;

      /* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":263
 *                 if   t == NPY_BYTE:        f = "b"
 *                 elif t == NPY_UBYTE:       f = "B"
 *                 elif t == NPY_SHORT:       f = "h"             # <<<<<<<<<<<<<<
 *                 elif t == NPY_USHORT:      f = "H"
 *                 elif t == NPY_INT:         f = "i"
 */
      case NPY_SHORT:
      __pyx_v_f = __pyx_k_h;
      break;

      /* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":264
 *                 elif t == NPY_UBYTE:       f = "B"
 *                 elif t == NPY_SHORT:       f = "h"
 *                 elif t == NPY_USHORT:      f = "H"             # <<<<<<<<<<<<<<
 *                 elif t == NPY_INT:         f = "i"
 *                 elif t == NPY_UINT:        f = "I"
 */
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      __pyx_v_f = __pyx_k_H;
      break;

      /* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":265
 *                 elif t == NPY_SHORT:       f = "h"
 *                 elif t == NPY_USHORT:      f = "H"
 *                 elif t == NPY_INT:         f = "i"             # <<<<<<<<<<<<<<
 *                 elif t == NPY_UINT:        f = "I"
 *                 elif t == NPY_LONG:        f = "l"
 */
      case NPY_INT:
      __pyx_v_f = __pyx_k_i;
      break;

      /* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":266
 *                 elif t == NPY_USHORT:      f = "H"
 *                 elif t == NPY_INT:         f = "i"
 *                 elif t == NPY_UINT:        f = "I"             # <<<<<<<<<<<<<<
 *                 elif t == NPY_LONG:        f = "l"
 *                 elif t == NPY_ULONG:       f = "L"
 */
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      break;

      /* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":267
 *                 elif t == NPY_INT:         f = "i"
 *                 elif t == NPY_UINT:        f = "I"
 *                 elif t == NPY_LONG:        f = "l"             # <<<<<<<<<<<<<<
 *                 elif t == NPY_ULONG:       f = "L"
 *                 elif t == NPY_LONGLONG:    f = "q"
 */
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      __pyx_v_f = __pyx_k_l;
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      /* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":268
 *                 elif t == NPY_UINT:        f = "I"
 *                 elif t == NPY_LONG:        f = "l"
 *                 elif t == NPY_ULONG:       f = "L"             # <<<<<<<<<<<<<<
 *                 elif t == NPY_LONGLONG:    f = "q"
 *                 elif t == NPY_ULONGLONG:   f = "Q"
 */
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      __pyx_v_f = __pyx_k_L;
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      /* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":269
 *                 elif t == NPY_LONG:        f = "l"
 *                 elif t == NPY_ULONG:       f = "L"
 *                 elif t == NPY_LONGLONG:    f = "q"             # <<<<<<<<<<<<<<
 *                 elif t == NPY_ULONGLONG:   f = "Q"
 *                 elif t == NPY_FLOAT:       f = "f"
 */
      case NPY_LONGLONG:
      __pyx_v_f = __pyx_k_q;
      break;

      /* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":270
 *                 elif t == NPY_ULONG:       f = "L"
 *                 elif t == NPY_LONGLONG:    f = "q"
 *                 elif t == NPY_ULONGLONG:   f = "Q"             # <<<<<<<<<<<<<<
 *                 elif t == NPY_FLOAT:       f = "f"
 *                 elif t == NPY_DOUBLE:      f = "d"
 */
      case NPY_ULONGLONG:
      __pyx_v_f = __pyx_k_Q;
      break;

      /* "C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\Cython\Includes\numpy\__init__.pxd":271
 *                 elif t == NPY_LONGLONG:    f = "q"
 *                 elif t == NPY_ULONGLONG:   f = "Q"
 *                 elif t == NPY_FLOAT:       f = "f"             # <<<<<<<<<<<<<<
 *                 elif t == NPY_DOUBLE:      f = "d"
 *                 elif t == NPY_LONGDOUBLE:  f = "g"
 */
      case NPY_FLOAT:
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 * 
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      /* "View.MemoryView":707
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      __pyx_t_10 = __Pyx_PyIndex_AsSsize_t(__pyx_v_index); if (unlikely((__pyx_t_10 == (Py_ssize_t)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 707; __pyx_clineno = __LINE__; goto __pyx_L1_error;}

      /* "View.MemoryView":704
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      /* "View.MemoryView":711
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      /* "View.MemoryView":712
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 *                                     memviewsliceobj.to_dtype_func,
 */
    __Pyx_XDECREF(((PyObject *)__pyx_r));

    /* "View.MemoryView":734
 *     if isinstance(memview, _memoryviewslice):
 *         return memoryview_fromslice(dst, new_ndim,
 *                                     memviewsliceobj.to_object_func,             # <<<<<<<<<<<<<<
 *                                     memviewsliceobj.to_dtype_func,
 *                                     memview.dtype_is_object)
 */
    if (unlikely(!__pyx_v_memviewsliceobj)) { __Pyx_RaiseUnboundLocalError("memviewsliceobj"); {__pyx_filename = __pyx_f[2]; __pyx_lineno = 734; __pyx_clineno = __LINE__; goto __pyx_L1_error;} }

    /* "View.MemoryView":735
 *         return memoryview_fromslice(dst, new_ndim,
 *                                     memviewsliceobj.to_object_func,
 *                                     memviewsliceobj.to_dtype_func,             # <<<<<<<<<<<<<<
 *                                     memview.dtype_is_object)
 *     else:
 */
    if (unlikely(!__pyx_v_memviewsliceobj)) { __Pyx_RaiseUnboundLocalError("memviewsliceobj"); {__pyx_filename = __pyx_f[2]; __pyx_lineno = 735; __pyx_clineno = __LINE__; goto __pyx_L1_error;} }

    /* "View.MemoryView":733
 * 
 *     if isinstance(memview, _memoryviewslice):
 *         return memoryview_fromslice(dst, new_ndim,             # <<<<<<<<<<<<<<
 *                                     memviewsliceobj.to_object_func,
 *                                     memviewsliceobj.to_dtype_func,
 */
    __pyx_t_3 = __pyx_memoryview_fromslice(__pyx_v_dst, __pyx_v_new_ndim, __pyx_v_memviewsliceobj->to_object_func, __pyx_v_memviewsliceobj->to_dtype_func, __pyx_v_memview->dtype_is_object); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 733; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
    __Pyx_GOTREF(__pyx_t_3);
    if (!(likely(((__pyx_t_3) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_3, __pyx_memoryview_type))))) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 733; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
    __pyx_r = ((struct __pyx_memoryview_obj *)__pyx_t_3);
    __pyx_t_3 = 0;
    goto __pyx_L0;
  }
  /*else*/ {

    /* "View.MemoryView":738
 *                                     memview.dtype_is_object)
 *     else:
 *         return memoryview_fromslice(dst, new_ndim, NULL, NULL,             # <<<<<<<<<<<<<<
 *                                     memview.dtype_is_object)
 * 
 */
    __Pyx_XDECREF(((PyObject *)__pyx_r));

    /* "View.MemoryView":739
 *     else:
 *         return memoryview_fromslice(dst, new_ndim, NULL, NULL,
 *                                     memview.dtype_is_object)             # <<<<<<<<<<<<<<
 * 
 * 
 */
    __pyx_t_3 = __pyx_memoryview_fromslice(__pyx_v_dst, __pyx_v_new_ndim, NULL, NULL, __pyx_v_memview->dtype_is_object); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 738; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
    __Pyx_GOTREF(__pyx_t_3);

    /* "View.MemoryView":738
 *                                     memview.dtype_is_object)
 *     else:
 *         return memoryview_fromslice(dst, new_ndim, NULL, NULL,             # <<<<<<<<<<<<<<
 *                                     memview.dtype_is_object)
 * 
 */
    if (!(likely(((__pyx_t_3) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_3, __pyx_memoryview_type))))) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 738; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
    __pyx_r = ((struct __pyx_memoryview_obj *)__pyx_t_3);
    __pyx_t_3 = 0;
    goto __pyx_L0;
  }

  /* "View.MemoryView":666
 * 
 * @cname('__pyx_memview_slice')
 * cdef memoryview memview_slice(memoryview memview, object indices):             # <<<<<<<<<<<<<<
 *     cdef int new_ndim = 0, suboffset_dim = -1, dim
 *     cdef bint negative_step
 */

  /* function exit code */
  __pyx_L1_error:;
  __Pyx_XDECREF(__pyx_t_3);
  __Pyx_XDECREF(__pyx_t_9);
  __Pyx_AddTraceback("View.MemoryView.memview_slice", __pyx_clineno, __pyx_lineno, __pyx_filename);
  __pyx_r = 0;
  __pyx_L0:;
  __Pyx_XDECREF((PyObject *)__pyx_v_memviewsliceobj);
  __Pyx_XDECREF(__pyx_v_index);
  __Pyx_XGIVEREF((PyObject *)__pyx_r);
  __Pyx_RefNannyFinishContext();
  return __pyx_r;
}

/* "View.MemoryView":763
 * 
 * @cname('__pyx_memoryview_slice_memviewslice')
 * cdef int slice_memviewslice(             # <<<<<<<<<<<<<<
 *         __Pyx_memviewslice *dst,
 *         Py_ssize_t shape, Py_ssize_t stride, Py_ssize_t suboffset,
 */

static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, Py_ssize_t __pyx_v_shape, Py_ssize_t __pyx_v_stride, Py_ssize_t __pyx_v_suboffset, int __pyx_v_dim, int __pyx_v_new_ndim, int *__pyx_v_suboffset_dim, Py_ssize_t __pyx_v_start, Py_ssize_t __pyx_v_stop, Py_ssize_t __pyx_v_step, int __pyx_v_have_start, int __pyx_v_have_stop, int __pyx_v_have_step, int __pyx_v_is_slice) {
  Py_ssize_t __pyx_v_new_shape;
  int __pyx_v_negative_step;
  int __pyx_r;
  int __pyx_t_1;
  int __pyx_t_2;
  int __pyx_t_3;
  int __pyx_lineno = 0;
  const char *__pyx_filename = NULL;
  int __pyx_clineno = 0;

  /* "View.MemoryView":783
 *     cdef bint negative_step
 * 
 *     if not is_slice:             # <<<<<<<<<<<<<<
 * 
 *         if start < 0:
 */
  __pyx_t_1 = ((!(__pyx_v_is_slice != 0)) != 0);
  if (__pyx_t_1) {

    /* "View.MemoryView":785
 *     if not is_slice:
 * 
 *         if start < 0:             # <<<<<<<<<<<<<<
 *             start += shape
 *         if not 0 <= start < shape:
 */
    __pyx_t_1 = ((__pyx_v_start < 0) != 0);
    if (__pyx_t_1) {

      /* "View.MemoryView":786
 * 
 *         if start < 0:
 *             start += shape             # <<<<<<<<<<<<<<
 *         if not 0 <= start < shape:
 *             _err_dim(IndexError, "Index out of bounds (axis %d)", dim)
 */
      __pyx_v_start = (__pyx_v_start + __pyx_v_shape);
      goto __pyx_L4;
    }
    __pyx_L4:;

    /* "View.MemoryView":787
 *         if start < 0:
 *             start += shape
 *         if not 0 <= start < shape:             # <<<<<<<<<<<<<<
 *             _err_dim(IndexError, "Index out of bounds (axis %d)", dim)
 *     else:
 */
    __pyx_t_1 = (0 <= __pyx_v_start);
    if (__pyx_t_1) {
      __pyx_t_1 = (__pyx_v_start < __pyx_v_shape);
    }
    __pyx_t_2 = ((!(__pyx_t_1 != 0)) != 0);
    if (__pyx_t_2) {

      /* "View.MemoryView":788
 *             start += shape
 *         if not 0 <= start < shape:
 *             _err_dim(IndexError, "Index out of bounds (axis %d)", dim)             # <<<<<<<<<<<<<<
 *     else:
 * 
 */
      __pyx_t_3 = __pyx_memoryview_err_dim(__pyx_builtin_IndexError, __pyx_k_Index_out_of_bounds_axis_d, __pyx_v_dim); if (unlikely(__pyx_t_3 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 788; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
      goto __pyx_L5;
    }
    __pyx_L5:;
    goto __pyx_L3;
  }
  /*else*/ {

    /* "View.MemoryView":791
 *     else:
 * 
 *         negative_step = have_step != 0 and step < 0             # <<<<<<<<<<<<<<
 * 
 *         if have_step and step == 0:
 */
    __pyx_t_1 = ((__pyx_v_have_step != 0) != 0);
    if (__pyx_t_1) {
    } else {
      __pyx_t_2 = __pyx_t_1;
      goto __pyx_L6_bool_binop_done;
    }
    __pyx_t_1 = ((__pyx_v_step < 0) != 0);
    __pyx_t_2 = __pyx_t_1;
    __pyx_L6_bool_binop_done:;
    __pyx_v_negative_step = __pyx_t_2;

    /* "View.MemoryView":793
 *         negative_step = have_step != 0 and step < 0
 * 
 *         if have_step and step == 0:             # <<<<<<<<<<<<<<
 *             _err_dim(ValueError, "Step may not be zero (axis %d)", dim)
 * 
 */
    __pyx_t_1 = (__pyx_v_have_step != 0);
    if (__pyx_t_1) {
    } else {
      __pyx_t_2 = __pyx_t_1;
      goto __pyx_L9_bool_binop_done;
    }
    __pyx_t_1 = ((__pyx_v_step == 0) != 0);
    __pyx_t_2 = __pyx_t_1;
    __pyx_L9_bool_binop_done:;
    if (__pyx_t_2) {

      /* "View.MemoryView":794
 * 
 *         if have_step and step == 0:
 *             _err_dim(ValueError, "Step may not be zero (axis %d)", dim)             # <<<<<<<<<<<<<<
 * 
 * 
 */
      __pyx_t_3 = __pyx_memoryview_err_dim(__pyx_builtin_ValueError, __pyx_k_Step_may_not_be_zero_axis_d, __pyx_v_dim); if (unlikely(__pyx_t_3 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 794; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
      goto __pyx_L8;
    }
    __pyx_L8:;

    /* "View.MemoryView":797
 * 
 * 
 *         if have_start:             # <<<<<<<<<<<<<<
 *             if start < 0:
 *                 start += shape
 */
    __pyx_t_2 = (__pyx_v_have_start != 0);
    if (__pyx_t_2) {

      /* "View.MemoryView":798
 * 
 *         if have_start:
 *             if start < 0:             # <<<<<<<<<<<<<<
 *                 start += shape
 *                 if start < 0:
 */
      __pyx_t_2 = ((__pyx_v_start < 0) != 0);
      if (__pyx_t_2) {

        /* "View.MemoryView":799
 *         if have_start:
 *             if start < 0:
 *                 start += shape             # <<<<<<<<<<<<<<
 *                 if start < 0:
 *                     start = 0
 */
        __pyx_v_start = (__pyx_v_start + __pyx_v_shape);

        /* "View.MemoryView":800
 *             if start < 0:
 *                 start += shape
 *                 if start < 0:             # <<<<<<<<<<<<<<
 *                     start = 0
 *             elif start >= shape:
 */
        __pyx_t_2 = ((__pyx_v_start < 0) != 0);
        if (__pyx_t_2) {

          /* "View.MemoryView":801
 *                 start += shape
 *                 if start < 0:
 *                     start = 0             # <<<<<<<<<<<<<<
 *             elif start >= shape:
 *                 if negative_step:
 */
          __pyx_v_start = 0;
          goto __pyx_L13;
        }
        __pyx_L13:;
        goto __pyx_L12;
      }

      /* "View.MemoryView":802
 *                 if start < 0:
 *                     start = 0
 *             elif start >= shape:             # <<<<<<<<<<<<<<
 *                 if negative_step:
 *                     start = shape - 1
 */
      __pyx_t_2 = ((__pyx_v_start >= __pyx_v_shape) != 0);
      if (__pyx_t_2) {

        /* "View.MemoryView":803
 *                     start = 0
 *             elif start >= shape:
 *                 if negative_step:             # <<<<<<<<<<<<<<
 *                     start = shape - 1
 *                 else:
 */
        __pyx_t_2 = (__pyx_v_negative_step != 0);
        if (__pyx_t_2) {

          /* "View.MemoryView":804
 *             elif start >= shape:
 *                 if negative_step:
 *                     start = shape - 1             # <<<<<<<<<<<<<<
 *                 else:
 *                     start = shape
 */
          __pyx_v_start = (__pyx_v_shape - 1);
          goto __pyx_L14;
        }
        /*else*/ {

          /* "View.MemoryView":806
 *                     start = shape - 1
 *                 else:
 *                     start = shape             # <<<<<<<<<<<<<<
 *         else:
 *             if negative_step:
 */
          __pyx_v_start = __pyx_v_shape;
        }
        __pyx_L14:;
        goto __pyx_L12;
      }
      __pyx_L12:;
      goto __pyx_L11;
    }
    /*else*/ {

      /* "View.MemoryView":808
 *                     start = shape
 *         else:
 *             if negative_step:             # <<<<<<<<<<<<<<
 *                 start = shape - 1
 *             else:
 */
      __pyx_t_2 = (__pyx_v_negative_step != 0);
      if (__pyx_t_2) {

        /* "View.MemoryView":809
 *         else:
 *             if negative_step:
 *                 start = shape - 1             # <<<<<<<<<<<<<<
 *             else:
 *                 start = 0
 */
        __pyx_v_start = (__pyx_v_shape - 1);
        goto __pyx_L15;
      }
      /*else*/ {

        /* "View.MemoryView":811
 *                 start = shape - 1
 *             else:
 *                 start = 0             # <<<<<<<<<<<<<<
 * 
 *         if have_stop:
 */
        __pyx_v_start = 0;
      }
      __pyx_L15:;
    }
    __pyx_L11:;

    /* "View.MemoryView":813
 *                 start = 0
 * 
 *         if have_stop:             # <<<<<<<<<<<<<<
 *             if stop < 0:
 *                 stop += shape
 */
    __pyx_t_2 = (__pyx_v_have_stop != 0);
    if (__pyx_t_2) {

      /* "View.MemoryView":814
 * 
 *         if have_stop:
 *             if stop < 0:             # <<<<<<<<<<<<<<
 *                 stop += shape
 *                 if stop < 0:
 */
      __pyx_t_2 = ((__pyx_v_stop < 0) != 0);
      if (__pyx_t_2) {

        /* "View.MemoryView":815
 *         if have_stop:
 *             if stop < 0:
 *                 stop += shape             # <<<<<<<<<<<<<<
 *                 if stop < 0:
 *                     stop = 0
 */
        __pyx_v_stop = (__pyx_v_stop + __pyx_v_shape);

        /* "View.MemoryView":816
 *             if stop < 0:
 *                 stop += shape
 *                 if stop < 0:             # <<<<<<<<<<<<<<
 *                     stop = 0
 *             elif stop > shape:
 */
        __pyx_t_2 = ((__pyx_v_stop < 0) != 0);
        if (__pyx_t_2) {

          /* "View.MemoryView":817
 *                 stop += shape
 *                 if stop < 0:
 *                     stop = 0             # <<<<<<<<<<<<<<
 *             elif stop > shape:
 *                 stop = shape
 */
          __pyx_v_stop = 0;
          goto __pyx_L18;
        }
        __pyx_L18:;
        goto __pyx_L17;
      }

      /* "View.MemoryView":818
 *                 if stop < 0:
 *                     stop = 0
 *             elif stop > shape:             # <<<<<<<<<<<<<<
 *                 stop = shape
 *         else:
 */
      __pyx_t_2 = ((__pyx_v_stop > __pyx_v_shape) != 0);
      if (__pyx_t_2) {

        /* "View.MemoryView":819
 *                     stop = 0
 *             elif stop > shape:
 *                 stop = shape             # <<<<<<<<<<<<<<
 *         else:
 *             if negative_step:
 */
        __pyx_v_stop = __pyx_v_shape;
        goto __pyx_L17;
      }
      __pyx_L17:;
      goto __pyx_L16;
    }
    /*else*/ {

      /* "View.MemoryView":821
 *                 stop = shape
 *         else:
 *             if negative_step:             # <<<<<<<<<<<<<<
 *                 stop = -1
 *             else:
 */
      __pyx_t_2 = (__pyx_v_negative_step != 0);
      if (__pyx_t_2) {

        /* "View.MemoryView":822
 *         else:
 *             if negative_step:
 *                 stop = -1             # <<<<<<<<<<<<<<
 *             else:
 *                 stop = shape
 */
        __pyx_v_stop = -1;
        goto __pyx_L19;
      }
      /*else*/ {

        /* "View.MemoryView":824
 *                 stop = -1
 *             else:
 *                 stop = shape             # <<<<<<<<<<<<<<
 * 
 *         if not have_step:
 */
        __pyx_v_stop = __pyx_v_shape;
      }
      __pyx_L19:;
    }
    __pyx_L16:;

    /* "View.MemoryView":826
 *                 stop = shape
 * 
 *         if not have_step:             # <<<<<<<<<<<<<<
 *             step = 1
 * 
 */
    __pyx_t_2 = ((!(__pyx_v_have_step != 0)) != 0);
    if (__pyx_t_2) {

      /* "View.MemoryView":827
 * 
 *         if not have_step:
 *             step = 1             # <<<<<<<<<<<<<<
 * 
 * 
 */
      __pyx_v_step = 1;
      goto __pyx_L20;
    }
    __pyx_L20:;

    /* "View.MemoryView":831
 * 
 *         with cython.cdivision(True):
 *             new_shape = (stop - start) // step             # <<<<<<<<<<<<<<
 * 
 *             if (stop - start) - step * new_shape:
 */
    __pyx_v_new_shape = ((__pyx_v_stop - __pyx_v_start) / __pyx_v_step);

    /* "View.MemoryView":833
 *             new_shape = (stop - start) // step
 * 
 *             if (stop - start) - step * new_shape:             # <<<<<<<<<<<<<<
 *                 new_shape += 1
 * 
 */
    __pyx_t_2 = (((__pyx_v_stop - __pyx_v_start) - (__pyx_v_step * __pyx_v_new_shape)) != 0);
    if (__pyx_t_2) {

      /* "View.MemoryView":834
 * 
 *             if (stop - start) - step * new_shape:
 *                 new_shape += 1             # <<<<<<<<<<<<<<
 * 
 *         if new_shape < 0:
 */
      __pyx_v_new_shape = (__pyx_v_new_shape + 1);
      goto __pyx_L21;
    }
    __pyx_L21:;

    /* "View.MemoryView":836
 *                 new_shape += 1
 * 
 *         if new_shape < 0:             # <<<<<<<<<<<<<<
 *             new_shape = 0
 * 
 */
    __pyx_t_2 = ((__pyx_v_new_shape < 0) != 0);
    if (__pyx_t_2) {

      /* "View.MemoryView":837
 * 
 *         if new_shape < 0:
 *             new_shape = 0             # <<<<<<<<<<<<<<
 * 
 * 
 */
      __pyx_v_new_shape = 0;
      goto __pyx_L22;
    }
    __pyx_L22:;

    /* "View.MemoryView":840
 * 
 * 
 *         dst.strides[new_ndim] = stride * step             # <<<<<<<<<<<<<<
 *         dst.shape[new_ndim] = new_shape
 *         dst.suboffsets[new_ndim] = suboffset
 */
    (__pyx_v_dst->strides[__pyx_v_new_ndim]) = (__pyx_v_stride * __pyx_v_step);

    /* "View.MemoryView":841
 * 
 *         dst.strides[new_ndim] = stride * step
 *         dst.shape[new_ndim] = new_shape             # <<<<<<<<<<<<<<
 *         dst.suboffsets[new_ndim] = suboffset
 * 
 */
    (__pyx_v_dst->shape[__pyx_v_new_ndim]) = __pyx_v_new_shape;

    /* "View.MemoryView":842
 *         dst.strides[new_ndim] = stride * step
 *         dst.shape[new_ndim] = new_shape
 *         dst.suboffsets[new_ndim] = suboffset             # <<<<<<<<<<<<<<
 * 
 * 
 */
    (__pyx_v_dst->suboffsets[__pyx_v_new_ndim]) = __pyx_v_suboffset;
  }
  __pyx_L3:;

  /* "View.MemoryView":845
 * 
 * 
 *     if suboffset_dim[0] < 0:             # <<<<<<<<<<<<<<
 *         dst.data += start * stride
 *     else:
 */
  __pyx_t_2 = (((__pyx_v_suboffset_dim[0]) < 0) != 0);
  if (__pyx_t_2) {

    /* "View.MemoryView":846
 * 
 *     if suboffset_dim[0] < 0:
 *         dst.data += start * stride             # <<<<<<<<<<<<<<
 *     else:
 *         dst.suboffsets[suboffset_dim[0]] += start * stride
 */
    __pyx_v_dst->data = (__pyx_v_dst->data + (__pyx_v_start * __pyx_v_stride));
    goto __pyx_L23;
  }
  /*else*/ {

    /* "View.MemoryView":848
 *         dst.data += start * stride
 *     else:
 *         dst.suboffsets[suboffset_dim[0]] += start * stride             # <<<<<<<<<<<<<<
 * 
 *     if suboffset >= 0:
 */
    __pyx_t_3 = (__pyx_v_suboffset_dim[0]);
    (__pyx_v_dst->suboffsets[__pyx_t_3]) = ((__pyx_v_dst->suboffsets[__pyx_t_3]) + (__pyx_v_start * __pyx_v_stride));
  }
  __pyx_L23:;

  /* "View.MemoryView":850
 *         dst.suboffsets[suboffset_dim[0]] += start * stride
 * 
 *     if suboffset >= 0:             # <<<<<<<<<<<<<<
 *         if not is_slice:
 *             if new_ndim == 0:
 */
  __pyx_t_2 = ((__pyx_v_suboffset >= 0) != 0);
  if (__pyx_t_2) {

    /* "View.MemoryView":851
 * 
 *     if suboffset >= 0:
 *         if not is_slice:             # <<<<<<<<<<<<<<
 *             if new_ndim == 0:
 *                 dst.data = (<char **> dst.data)[0] + suboffset
 */
    __pyx_t_2 = ((!(__pyx_v_is_slice != 0)) != 0);
    if (__pyx_t_2) {

      /* "View.MemoryView":852
 *     if suboffset >= 0:
 *         if not is_slice:
 *             if new_ndim == 0:             # <<<<<<<<<<<<<<
 *                 dst.data = (<char **> dst.data)[0] + suboffset
 *             else:
 */
      __pyx_t_2 = ((__pyx_v_new_ndim == 0) != 0);
      if (__pyx_t_2) {

        /* "View.MemoryView":853
 *         if not is_slice:
 *             if new_ndim == 0:
 *                 dst.data = (<char **> dst.data)[0] + suboffset             # <<<<<<<<<<<<<<
 *             else:
 *                 _err_dim(IndexError, "All dimensions preceding dimension %d "
 */
        __pyx_v_dst->data = ((((char **)__pyx_v_dst->data)[0]) + __pyx_v_suboffset);
        goto __pyx_L26;
      }
      /*else*/ {

        /* "View.MemoryView":855
 *                 dst.data = (<char **> dst.data)[0] + suboffset
 *             else:
 *                 _err_dim(IndexError, "All dimensions preceding dimension %d "             # <<<<<<<<<<<<<<
 *                                      "must be indexed and not sliced", dim)
 *         else:
 */
        __pyx_t_3 = __pyx_memoryview_err_dim(__pyx_builtin_IndexError, __pyx_k_All_dimensions_preceding_dimensi, __pyx_v_dim); if (unlikely(__pyx_t_3 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 855; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
      }
      __pyx_L26:;
      goto __pyx_L25;
    }
    /*else*/ {

      /* "View.MemoryView":858
 *                                      "must be indexed and not sliced", dim)
 *         else:
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 *     else:
 */
  __pyx_t_2 = ((abs_py_ssize_t(__pyx_v_c_stride) <= abs_py_ssize_t(__pyx_v_f_stride)) != 0);
  if (__pyx_t_2) {

    /* "View.MemoryView":1089
 * 
 *     if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride):
 *         return 'C'             # <<<<<<<<<<<<<<
 *     else:
 *         return 'F'
 */
    __pyx_r = 'C';
    goto __pyx_L0;
  }
  /*else*/ {

    /* "View.MemoryView":1091
 *         return 'C'
 *     else:
 *         return 'F'             # <<<<<<<<<<<<<<
 * 
 * @cython.cdivision(True)
 */
    __pyx_r = 'F';
    goto __pyx_L0;
  }

  /* "View.MemoryView":1070
 * 
 * @cname('__pyx_get_best_slice_order')
 * cdef char get_best_order(__Pyx_memviewslice *mslice, int ndim) nogil:             # <<<<<<<<<<<<<<
 *     """
 *     Figure out the best memory access order for a given slice.
 */

  /* function exit code */
  __pyx_L0:;
  return __pyx_r;
}

/* "View.MemoryView":1094
 * 
 * @cython.cdivision(True)
 * cdef void _copy_strided_to_strided(char *src_data, Py_ssize_t *src_strides,             # <<<<<<<<<<<<<<
 *                                    char *dst_data, Py_ssize_t *dst_strides,
 *                                    Py_ssize_t *src_shape, Py_ssize_t *dst_shape,
 */

static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v_src_strides, char *__pyx_v_dst_data, Py_ssize_t *__pyx_v_dst_strides, Py_ssize_t *__pyx_v_src_shape, Py_ssize_t *__pyx_v_dst_shape, int __pyx_v_ndim, size_t __pyx_v_itemsize) {
  CYTHON_UNUSED Py_ssize_t __pyx_v_i;
  CYTHON_UNUSED Py_ssize_t __pyx_v_src_extent;
  Py_ssize_t __pyx_v_dst_extent;
  Py_ssize_t __pyx_v_src_stride;
  Py_ssize_t __pyx_v_dst_stride;
  int __pyx_t_1;
  int __pyx_t_2;
  int __pyx_t_3;
  Py_ssize_t __pyx_t_4;
  Py_ssize_t __pyx_t_5;

  /* "View.MemoryView":1101
 * 
 *     cdef Py_ssize_t i
 *     cdef Py_ssize_t src_extent = src_shape[0]             # <<<<<<<<<<<<<<
 *     cdef Py_ssize_t dst_extent = dst_shape[0]
 *     cdef Py_ssize_t src_stride = src_strides[0]
 */
  __pyx_v_src_extent = (__pyx_v_src_shape[0]);

  /* "View.MemoryView":1102
 *     cdef Py_ssize_t i
 *     cdef Py_ssize_t src_extent = src_shape[0]
 *     cdef Py_ssize_t dst_extent = dst_shape[0]             # <<<<<<<<<<<<<<
 *     cdef Py_ssize_t src_stride = src_strides[0]
 *     cdef Py_ssize_t dst_stride = dst_strides[0]
 */
  __pyx_v_dst_extent = (__pyx_v_dst_shape[0]);

  /* "View.MemoryView":1103
 *     cdef Py_ssize_t src_extent = src_shape[0]
 *     cdef Py_ssize_t dst_extent = dst_shape[0]
 *     cdef Py_ssize_t src_stride = src_strides[0]             # <<<<<<<<<<<<<<
 *     cdef Py_ssize_t dst_stride = dst_strides[0]
 * 
 */
  __pyx_v_src_stride = (__pyx_v_src_strides[0]);

  /* "View.MemoryView":1104
 *     cdef Py_ssize_t dst_extent = dst_shape[0]
 *     cdef Py_ssize_t src_stride = src_strides[0]
 *     cdef Py_ssize_t dst_stride = dst_strides[0]             # <<<<<<<<<<<<<<
 * 
 *     if ndim == 1:
 */
  __pyx_v_dst_stride = (__pyx_v_dst_strides[0]);

  /* "View.MemoryView":1106
 *     cdef Py_ssize_t dst_stride = dst_strides[0]
 * 
 *     if ndim == 1:             # <<<<<<<<<<<<<<
 *        if (src_stride > 0 and dst_stride > 0 and
 *            <size_t> src_stride == itemsize == <size_t> dst_stride):
 */
  __pyx_t_1 = ((__pyx_v_ndim == 1) != 0);
  if (__pyx_t_1) {

    /* "View.MemoryView":1107
 * 
 *     if ndim == 1:
 *        if (src_stride > 0 and dst_stride > 0 and             # <<<<<<<<<<<<<<
 *            <size_t> src_stride == itemsize == <size_t> dst_stride):
 *            memcpy(dst_data, src_data, itemsize * dst_extent)
 */
    __pyx_t_2 = ((__pyx_v_src_stride > 0) != 0);
    if (__pyx_t_2) {
    } else {
      __pyx_t_1 = __pyx_t_2;
      goto __pyx_L5_bool_binop_done;
    }
    __pyx_t_2 = ((__pyx_v_dst_stride > 0) != 0);
    if (__pyx_t_2) {
    } else {
      __pyx_t_1 = __pyx_t_2;
      goto __pyx_L5_bool_binop_done;
    }

    /* "View.MemoryView":1108
 *     if ndim == 1:
 *        if (src_stride > 0 and dst_stride > 0 and
 *            <size_t> src_stride == itemsize == <size_t> dst_stride):             # <<<<<<<<<<<<<<
 *            memcpy(dst_data, src_data, itemsize * dst_extent)
 *        else:
 */
    __pyx_t_2 = (((size_t)__pyx_v_src_stride) == __pyx_v_itemsize);
    if (__pyx_t_2) {
      __pyx_t_2 = (__pyx_v_itemsize == ((size_t)__pyx_v_dst_stride));
    }
    __pyx_t_3 = (__pyx_t_2 != 0);
    __pyx_t_1 = __pyx_t_3;
    __pyx_L5_bool_binop_done:;
    if (__pyx_t_1) {

      /* "View.MemoryView":1109
 *        if (src_stride > 0 and dst_stride > 0 and
 *            <size_t> src_stride == itemsize == <size_t> dst_stride):
 *            memcpy(dst_data, src_data, itemsize * dst_extent)             # <<<<<<<<<<<<<<
 *        else:
 *            for i in range(dst_extent):
 */
      memcpy(__pyx_v_dst_data, __pyx_v_src_data, (__pyx_v_itemsize * __pyx_v_dst_extent));
      goto __pyx_L4;
    }
    /*else*/ {

      /* "View.MemoryView":1111
 *            memcpy(dst_data, src_data, itemsize * dst_extent)
 *        else:
 *            for i in range(dst_extent):             # <<<<<<<<<<<<<<
 *                memcpy(dst_data, src_data, itemsize)
 *                src_data += src_stride
 */
      __pyx_t_4 = __pyx_v_dst_extent;
      for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) {
        __pyx_v_i = __pyx_t_5;

        /* "View.MemoryView":1112
 *        else:
 *            for i in range(dst_extent):
 *                memcpy(dst_data, src_data, itemsize)             # <<<<<<<<<<<<<<
 *                src_data += src_stride
 *                dst_data += dst_stride
 */
        memcpy(__pyx_v_dst_data, __pyx_v_src_data, __pyx_v_itemsize);

        /* "View.MemoryView":1113
 *            for i in range(dst_extent):
 *                memcpy(dst_data, src_data, itemsize)
 *                src_data += src_stride             # <<<<<<<<<<<<<<
 *                dst_data += dst_stride
 *     else:
 */
        __pyx_v_src_data = (__pyx_v_src_data + __pyx_v_src_stride);

        /* "View.MemoryView":1114
 *                memcpy(dst_data, src_data, itemsize)
 *                src_data += src_stride
 *                dst_data += dst_stride             # <<<<<<<<<<<<<<
 *     else:
 *         for i in range(dst_extent):
 */
        __pyx_v_dst_data = (__pyx_v_dst_data + __pyx_v_dst_stride);
      }
    }
    __pyx_L4:;
    goto __pyx_L3;
  }
  /*else*/ {

    /* "View.MemoryView":1116
 *                dst_data += dst_stride
 *     else:
 *         for i in range(dst_extent):             # <<<<<<<<<<<<<<
 *             _copy_strided_to_strided(src_data, src_strides + 1,
 *                                      dst_data, dst_strides + 1,
 */
    __pyx_t_4 = __pyx_v_dst_extent;
    for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) {
      __pyx_v_i = __pyx_t_5;

      /* "View.MemoryView":1117
 *     else:
 *         for i in range(dst_extent):
 *             _copy_strided_to_strided(src_data, src_strides + 1,             # <<<<<<<<<<<<<<
 *                                      dst_data, dst_strides + 1,
 *                                      src_shape + 1, dst_shape + 1,
 */
      _copy_strided_to_strided(__pyx_v_src_data, (__pyx_v_src_strides + 1), __pyx_v_dst_data, (__pyx_v_dst_strides + 1), (__pyx_v_src_shape + 1), (__pyx_v_dst_shape + 1), (__pyx_v_ndim - 1), __pyx_v_itemsize);

      /* "View.MemoryView":1121
 *                                      src_shape + 1, dst_shape + 1,
 *                                      ndim - 1, itemsize)
 *             src_data += src_stride             # <<<<<<<<<<<<<<
 *             dst_data += dst_stride
 * 
 */
      __pyx_v_src_data = (__pyx_v_src_data + __pyx_v_src_stride);

      /* "View.MemoryView":1122
 *                                      ndim - 1, itemsize)
 *             src_data += src_stride
 *             dst_data += dst_stride             # <<<<<<<<<<<<<<
 * 
 * cdef void copy_strided_to_strided(__Pyx_memviewslice *src,
 */
      __pyx_v_dst_data = (__pyx_v_dst_data + __pyx_v_dst_stride);
    }
  }
  __pyx_L3:;

  /* "View.MemoryView":1094
 * 
 * @cython.cdivision(True)
 * cdef void _copy_strided_to_strided(char *src_data, Py_ssize_t *src_strides,             # <<<<<<<<<<<<<<
 *                                    char *dst_data, Py_ssize_t *dst_strides,
 *                                    Py_ssize_t *src_shape, Py_ssize_t *dst_shape,
 */

  /* function exit code */
}

/* "View.MemoryView":1124
 *             dst_data += dst_stride
 * 
 * cdef void copy_strided_to_strided(__Pyx_memviewslice *src,             # <<<<<<<<<<<<<<
 *                                   __Pyx_memviewslice *dst,
 *                                   int ndim, size_t itemsize) nogil:
 */

static void copy_strided_to_strided(__Pyx_memviewslice *__pyx_v_src, __Pyx_memviewslice *__pyx_v_dst, int __pyx_v_ndim, size_t __pyx_v_itemsize) {

  /* "View.MemoryView":1127
 *                                   __Pyx_memviewslice *dst,
 *                                   int ndim, size_t itemsize) nogil:
 *     _copy_strided_to_strided(src.data, src.strides, dst.data, dst.strides,             # <<<<<<<<<<<<<<
 *                              src.shape, dst.shape, ndim, itemsize)
 * 
 */
  _copy_strided_to_strided(__pyx_v_src->data, __pyx_v_src->strides, __pyx_v_dst->data, __pyx_v_dst->strides, __pyx_v_src->shape, __pyx_v_dst->shape, __pyx_v_ndim, __pyx_v_itemsize);

  /* "View.MemoryView":1124
 *             dst_data += dst_stride
 * 
 * cdef void copy_strided_to_strided(__Pyx_memviewslice *src,             # <<<<<<<<<<<<<<
 *                                   __Pyx_memviewslice *dst,
 *                                   int ndim, size_t itemsize) nogil:
 */

  /* function exit code */
}

/* "View.MemoryView":1131
 * 
 * @cname('__pyx_memoryview_slice_get_size')
 * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil:             # <<<<<<<<<<<<<<
 *     "Return the size of the memory occupied by the slice in number of bytes"
 *     cdef int i
 */

static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *__pyx_v_src, int __pyx_v_ndim) {
  int __pyx_v_i;
  Py_ssize_t __pyx_v_size;
  Py_ssize_t __pyx_r;
  Py_ssize_t __pyx_t_1;
  int __pyx_t_2;
  int __pyx_t_3;

  /* "View.MemoryView":1134
 *     "Return the size of the memory occupied by the slice in number of bytes"
 *     cdef int i
 *     cdef Py_ssize_t size = src.memview.view.itemsize             # <<<<<<<<<<<<<<
 * 
 *     for i in range(ndim):
 */
  __pyx_t_1 = __pyx_v_src->memview->view.itemsize;
  __pyx_v_size = __pyx_t_1;

  /* "View.MemoryView":1136
 *     cdef Py_ssize_t size = src.memview.view.itemsize
 * 
 *     for i in range(ndim):             # <<<<<<<<<<<<<<
 *         size *= src.shape[i]
 * 
 */
  __pyx_t_2 = __pyx_v_ndim;
  for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) {
    __pyx_v_i = __pyx_t_3;

    /* "View.MemoryView":1137
 * 
 *     for i in range(ndim):
 *         size *= src.shape[i]             # <<<<<<<<<<<<<<
 * 
 *     return size
 */
    __pyx_v_size = (__pyx_v_size * (__pyx_v_src->shape[__pyx_v_i]));
  }

  /* "View.MemoryView":1139
 *         size *= src.shape[i]
 * 
 *     return size             # <<<<<<<<<<<<<<
 * 
 * @cname('__pyx_fill_contig_strides_array')
 */
  __pyx_r = __pyx_v_size;
  goto __pyx_L0;

  /* "View.MemoryView":1131
 * 
 * @cname('__pyx_memoryview_slice_get_size')
 * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil:             # <<<<<<<<<<<<<<
 *     "Return the size of the memory occupied by the slice in number of bytes"
 *     cdef int i
 */

  /* function exit code */
  __pyx_L0:;
  return __pyx_r;
}

/* "View.MemoryView":1142
 * 
 * @cname('__pyx_fill_contig_strides_array')
 * cdef Py_ssize_t fill_contig_strides_array(             # <<<<<<<<<<<<<<
 *                 Py_ssize_t *shape, Py_ssize_t *strides, Py_ssize_t stride,
 *                 int ndim, char order) nogil:
 */

static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *__pyx_v_shape, Py_ssize_t *__pyx_v_strides, Py_ssize_t __pyx_v_stride, int __pyx_v_ndim, char __pyx_v_order) {
  int __pyx_v_idx;
  Py_ssize_t __pyx_r;
  int __pyx_t_1;
  int __pyx_t_2;
  int __pyx_t_3;

  /* "View.MemoryView":1151
 *     cdef int idx
 * 
 *     if order == 'F':             # <<<<<<<<<<<<<<
 *         for idx in range(ndim):
 *             strides[idx] = stride
 */
  __pyx_t_1 = ((__pyx_v_order == 'F') != 0);
  if (__pyx_t_1) {

    /* "View.MemoryView":1152
 * 
 *     if order == 'F':
 *         for idx in range(ndim):             # <<<<<<<<<<<<<<
 *             strides[idx] = stride
 *             stride = stride * shape[idx]
 */
    __pyx_t_2 = __pyx_v_ndim;
    for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) {
      __pyx_v_idx = __pyx_t_3;

      /* "View.MemoryView":1153
 *     if order == 'F':
 *         for idx in range(ndim):
 *             strides[idx] = stride             # <<<<<<<<<<<<<<
 *             stride = stride * shape[idx]
 *     else:
 */
      (__pyx_v_strides[__pyx_v_idx]) = __pyx_v_stride;

      /* "View.MemoryView":1154
 *         for idx in range(ndim):
 *             strides[idx] = stride
 *             stride = stride * shape[idx]             # <<<<<<<<<<<<<<
 *     else:
 *         for idx in range(ndim - 1, -1, -1):
 */
      __pyx_v_stride = (__pyx_v_stride * (__pyx_v_shape[__pyx_v_idx]));
    }
    goto __pyx_L3;
  }
  /*else*/ {

    /* "View.MemoryView":1156
 *             stride = stride * shape[idx]
 *     else:
 *         for idx in range(ndim - 1, -1, -1):             # <<<<<<<<<<<<<<
 *             strides[idx] = stride
 *             stride = stride * shape[idx]
 */
    for (__pyx_t_2 = (__pyx_v_ndim - 1); __pyx_t_2 > -1; __pyx_t_2-=1) {
      __pyx_v_idx = __pyx_t_2;

      /* "View.MemoryView":1157
 *     else:
 *         for idx in range(ndim - 1, -1, -1):
 *             strides[idx] = stride             # <<<<<<<<<<<<<<
 *             stride = stride * shape[idx]
 * 
 */
      (__pyx_v_strides[__pyx_v_idx]) = __pyx_v_stride;

      /* "View.MemoryView":1158
 *         for idx in range(ndim - 1, -1, -1):
 *             strides[idx] = stride
 *             stride = stride * shape[idx]             # <<<<<<<<<<<<<<
 * 
 *     return stride
 */
      __pyx_v_stride = (__pyx_v_stride * (__pyx_v_shape[__pyx_v_idx]));
    }
  }
  __pyx_L3:;

  /* "View.MemoryView":1160
 *             stride = stride * shape[idx]
 * 
 *     return stride             # <<<<<<<<<<<<<<
 * 
 * @cname('__pyx_memoryview_copy_data_to_temp')
 */
  __pyx_r = __pyx_v_stride;
  goto __pyx_L0;

  /* "View.MemoryView":1142
 * 
 * @cname('__pyx_fill_contig_strides_array')
 * cdef Py_ssize_t fill_contig_strides_array(             # <<<<<<<<<<<<<<
 *                 Py_ssize_t *shape, Py_ssize_t *strides, Py_ssize_t stride,
 *                 int ndim, char order) nogil:
 */

  /* function exit code */
  __pyx_L0:;
  return __pyx_r;
}

/* "View.MemoryView":1163
 * 
 * @cname('__pyx_memoryview_copy_data_to_temp')
 * cdef void *copy_data_to_temp(__Pyx_memviewslice *src,             # <<<<<<<<<<<<<<
 *                              __Pyx_memviewslice *tmpslice,
 *                              char order,
 */

static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, __Pyx_memviewslice *__pyx_v_tmpslice, char __pyx_v_order, int __pyx_v_ndim) {
  int __pyx_v_i;
  void *__pyx_v_result;
  size_t __pyx_v_itemsize;
  size_t __pyx_v_size;
  void *__pyx_r;
  Py_ssize_t __pyx_t_1;
  int __pyx_t_2;
  int __pyx_t_3;
  struct __pyx_memoryview_obj *__pyx_t_4;
  int __pyx_t_5;
  int __pyx_lineno = 0;
  const char *__pyx_filename = NULL;
  int __pyx_clineno = 0;

  /* "View.MemoryView":1174
 *     cdef void *result
 * 
 *     cdef size_t itemsize = src.memview.view.itemsize             # <<<<<<<<<<<<<<
 *     cdef size_t size = slice_get_size(src, ndim)
 * 
 */
  __pyx_t_1 = __pyx_v_src->memview->view.itemsize;
  __pyx_v_itemsize = __pyx_t_1;

  /* "View.MemoryView":1175
 * 
 *     cdef size_t itemsize = src.memview.view.itemsize
 *     cdef size_t size = slice_get_size(src, ndim)             # <<<<<<<<<<<<<<
 * 
 *     result = malloc(size)
 */
  __pyx_v_size = __pyx_memoryview_slice_get_size(__pyx_v_src, __pyx_v_ndim);

  /* "View.MemoryView":1177
 *     cdef size_t size = slice_get_size(src, ndim)
 * 
 *     result = malloc(size)             # <<<<<<<<<<<<<<
 *     if not result:
 *         _err(MemoryError, NULL)
 */
  __pyx_v_result = malloc(__pyx_v_size);

  /* "View.MemoryView":1178
 * 
 *     result = malloc(size)
 *     if not result:             # <<<<<<<<<<<<<<
 *         _err(MemoryError, NULL)
 * 
 */
  __pyx_t_2 = ((!(__pyx_v_result != 0)) != 0);
  if (__pyx_t_2) {

    /* "View.MemoryView":1179
 *     result = malloc(size)
 *     if not result:
 *         _err(MemoryError, NULL)             # <<<<<<<<<<<<<<
 * 
 * 
 */
    __pyx_t_3 = __pyx_memoryview_err(__pyx_builtin_MemoryError, NULL); if (unlikely(__pyx_t_3 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1179; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
    goto __pyx_L3;
  }
  __pyx_L3:;

  /* "View.MemoryView":1182
 * 
 * 
 *     tmpslice.data = <char *> result             # <<<<<<<<<<<<<<
 *     tmpslice.memview = src.memview
 *     for i in range(ndim):
 */
  __pyx_v_tmpslice->data = ((char *)__pyx_v_result);

  /* "View.MemoryView":1183
 * 
 *     tmpslice.data = <char *> result
 *     tmpslice.memview = src.memview             # <<<<<<<<<<<<<<
 *     for i in range(ndim):
 *         tmpslice.shape[i] = src.shape[i]
 */
  __pyx_t_4 = __pyx_v_src->memview;
  __pyx_v_tmpslice->memview = __pyx_t_4;

  /* "View.MemoryView":1184
 *     tmpslice.data = <char *> result
 *     tmpslice.memview = src.memview
 *     for i in range(ndim):             # <<<<<<<<<<<<<<
 *         tmpslice.shape[i] = src.shape[i]
 *         tmpslice.suboffsets[i] = -1
 */
  __pyx_t_3 = __pyx_v_ndim;
  for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_3; __pyx_t_5+=1) {
    __pyx_v_i = __pyx_t_5;

    /* "View.MemoryView":1185
 *     tmpslice.memview = src.memview
 *     for i in range(ndim):
 *         tmpslice.shape[i] = src.shape[i]             # <<<<<<<<<<<<<<
 *         tmpslice.suboffsets[i] = -1
 * 
 */
    (__pyx_v_tmpslice->shape[__pyx_v_i]) = (__pyx_v_src->shape[__pyx_v_i]);

    /* "View.MemoryView":1186
 *     for i in range(ndim):
 *         tmpslice.shape[i] = src.shape[i]
 *         tmpslice.suboffsets[i] = -1             # <<<<<<<<<<<<<<
 * 
 *     fill_contig_strides_array(&tmpslice.shape[0], &tmpslice.strides[0], itemsize,
 */
    (__pyx_v_tmpslice->suboffsets[__pyx_v_i]) = -1;
  }

  /* "View.MemoryView":1188
 *         tmpslice.suboffsets[i] = -1
 * 
 *     fill_contig_strides_array(&tmpslice.shape[0], &tmpslice.strides[0], itemsize,             # <<<<<<<<<<<<<<
 *                               ndim, order)
 * 
 */
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 *     cdef size_t itemsize = src.memview.view.itemsize
 *     cdef int i
 *     cdef char order = get_best_order(&src, src_ndim)             # <<<<<<<<<<<<<<
 *     cdef bint broadcasting = False
 *     cdef bint direct_copy = False
 */
  __pyx_v_order = __pyx_get_best_slice_order((&__pyx_v_src), __pyx_v_src_ndim);

  /* "View.MemoryView":1235
 *     cdef int i
 *     cdef char order = get_best_order(&src, src_ndim)
 *     cdef bint broadcasting = False             # <<<<<<<<<<<<<<
 *     cdef bint direct_copy = False
 *     cdef __Pyx_memviewslice tmp
 */
  __pyx_v_broadcasting = 0;

  /* "View.MemoryView":1236
 *     cdef char order = get_best_order(&src, src_ndim)
 *     cdef bint broadcasting = False
 *     cdef bint direct_copy = False             # <<<<<<<<<<<<<<
 *     cdef __Pyx_memviewslice tmp
 * 
 */
  __pyx_v_direct_copy = 0;

  /* "View.MemoryView":1239
 *     cdef __Pyx_memviewslice tmp
 * 
 *     if src_ndim < dst_ndim:             # <<<<<<<<<<<<<<
 *         broadcast_leading(&src, src_ndim, dst_ndim)
 *     elif dst_ndim < src_ndim:
 */
  __pyx_t_2 = ((__pyx_v_src_ndim < __pyx_v_dst_ndim) != 0);
  if (__pyx_t_2) {

    /* "View.MemoryView":1240
 * 
 *     if src_ndim < dst_ndim:
 *         broadcast_leading(&src, src_ndim, dst_ndim)             # <<<<<<<<<<<<<<
 *     elif dst_ndim < src_ndim:
 *         broadcast_leading(&dst, dst_ndim, src_ndim)
 */
    __pyx_memoryview_broadcast_leading((&__pyx_v_src), __pyx_v_src_ndim, __pyx_v_dst_ndim);
    goto __pyx_L3;
  }

  /* "View.MemoryView":1241
 *     if src_ndim < dst_ndim:
 *         broadcast_leading(&src, src_ndim, dst_ndim)
 *     elif dst_ndim < src_ndim:             # <<<<<<<<<<<<<<
 *         broadcast_leading(&dst, dst_ndim, src_ndim)
 * 
 */
  __pyx_t_2 = ((__pyx_v_dst_ndim < __pyx_v_src_ndim) != 0);
  if (__pyx_t_2) {

    /* "View.MemoryView":1242
 *         broadcast_leading(&src, src_ndim, dst_ndim)
 *     elif dst_ndim < src_ndim:
 *         broadcast_leading(&dst, dst_ndim, src_ndim)             # <<<<<<<<<<<<<<
 * 
 *     cdef int ndim = max(src_ndim, dst_ndim)
 */
    __pyx_memoryview_broadcast_leading((&__pyx_v_dst), __pyx_v_dst_ndim, __pyx_v_src_ndim);
    goto __pyx_L3;
  }
  __pyx_L3:;

  /* "View.MemoryView":1244
 *         broadcast_leading(&dst, dst_ndim, src_ndim)
 * 
 *     cdef int ndim = max(src_ndim, dst_ndim)             # <<<<<<<<<<<<<<
 * 
 *     for i in range(ndim):
 */
  __pyx_t_3 = __pyx_v_dst_ndim;
  __pyx_t_4 = __pyx_v_src_ndim;
  if (((__pyx_t_3 > __pyx_t_4) != 0)) {
    __pyx_t_5 = __pyx_t_3;
  } else {
    __pyx_t_5 = __pyx_t_4;
  }
  __pyx_v_ndim = __pyx_t_5;

  /* "View.MemoryView":1246
 *     cdef int ndim = max(src_ndim, dst_ndim)
 * 
 *     for i in range(ndim):             # <<<<<<<<<<<<<<
 *         if src.shape[i] != dst.shape[i]:
 *             if src.shape[i] == 1:
 */
  __pyx_t_5 = __pyx_v_ndim;
  for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_5; __pyx_t_3+=1) {
    __pyx_v_i = __pyx_t_3;

    /* "View.MemoryView":1247
 * 
 *     for i in range(ndim):
 *         if src.shape[i] != dst.shape[i]:             # <<<<<<<<<<<<<<
 *             if src.shape[i] == 1:
 *                 broadcasting = True
 */
    __pyx_t_2 = (((__pyx_v_src.shape[__pyx_v_i]) != (__pyx_v_dst.shape[__pyx_v_i])) != 0);
    if (__pyx_t_2) {

      /* "View.MemoryView":1248
 *     for i in range(ndim):
 *         if src.shape[i] != dst.shape[i]:
 *             if src.shape[i] == 1:             # <<<<<<<<<<<<<<
 *                 broadcasting = True
 *                 src.strides[i] = 0
 */
      __pyx_t_2 = (((__pyx_v_src.shape[__pyx_v_i]) == 1) != 0);
      if (__pyx_t_2) {

        /* "View.MemoryView":1249
 *         if src.shape[i] != dst.shape[i]:
 *             if src.shape[i] == 1:
 *                 broadcasting = True             # <<<<<<<<<<<<<<
 *                 src.strides[i] = 0
 *             else:
 */
        __pyx_v_broadcasting = 1;

        /* "View.MemoryView":1250
 *             if src.shape[i] == 1:
 *                 broadcasting = True
 *                 src.strides[i] = 0             # <<<<<<<<<<<<<<
 *             else:
 *                 _err_extents(i, dst.shape[i], src.shape[i])
 */
        (__pyx_v_src.strides[__pyx_v_i]) = 0;
        goto __pyx_L7;
      }
      /*else*/ {

        /* "View.MemoryView":1252
 *                 src.strides[i] = 0
 *             else:
 *                 _err_extents(i, dst.shape[i], src.shape[i])             # <<<<<<<<<<<<<<
 * 
 *         if src.suboffsets[i] >= 0:
 */
        __pyx_t_4 = __pyx_memoryview_err_extents(__pyx_v_i, (__pyx_v_dst.shape[__pyx_v_i]), (__pyx_v_src.shape[__pyx_v_i])); if (unlikely(__pyx_t_4 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1252; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
      }
      __pyx_L7:;
      goto __pyx_L6;
    }
    __pyx_L6:;

    /* "View.MemoryView":1254
 *                 _err_extents(i, dst.shape[i], src.shape[i])
 * 
 *         if src.suboffsets[i] >= 0:             # <<<<<<<<<<<<<<
 *             _err_dim(ValueError, "Dimension %d is not direct", i)
 * 
 */
    __pyx_t_2 = (((__pyx_v_src.suboffsets[__pyx_v_i]) >= 0) != 0);
    if (__pyx_t_2) {

      /* "View.MemoryView":1255
 * 
 *         if src.suboffsets[i] >= 0:
 *             _err_dim(ValueError, "Dimension %d is not direct", i)             # <<<<<<<<<<<<<<
 * 
 *     if slices_overlap(&src, &dst, ndim, itemsize):
 */
      __pyx_t_4 = __pyx_memoryview_err_dim(__pyx_builtin_ValueError, __pyx_k_Dimension_d_is_not_direct, __pyx_v_i); if (unlikely(__pyx_t_4 == -1)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1255; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
      goto __pyx_L8;
    }
    __pyx_L8:;
  }

  /* "View.MemoryView":1257
 *             _err_dim(ValueError, "Dimension %d is not direct", i)
 * 
 *     if slices_overlap(&src, &dst, ndim, itemsize):             # <<<<<<<<<<<<<<
 * 
 *         if not slice_is_contig(&src, order, ndim):
 */
  __pyx_t_2 = (__pyx_slices_overlap((&__pyx_v_src), (&__pyx_v_dst), __pyx_v_ndim, __pyx_v_itemsize) != 0);
  if (__pyx_t_2) {

    /* "View.MemoryView":1259
 *     if slices_overlap(&src, &dst, ndim, itemsize):
 * 
 *         if not slice_is_contig(&src, order, ndim):             # <<<<<<<<<<<<<<
 *             order = get_best_order(&dst, ndim)
 * 
 */
    __pyx_t_2 = ((!(__pyx_memviewslice_is_contig((&__pyx_v_src), __pyx_v_order, __pyx_v_ndim) != 0)) != 0);
    if (__pyx_t_2) {

      /* "View.MemoryView":1260
 * 
 *         if not slice_is_contig(&src, order, ndim):
 *             order = get_best_order(&dst, ndim)             # <<<<<<<<<<<<<<
 * 
 *         tmpdata = copy_data_to_temp(&src, &tmp, order, ndim)
 */
      __pyx_v_order = __pyx_get_best_slice_order((&__pyx_v_dst), __pyx_v_ndim);
      goto __pyx_L10;
    }
    __pyx_L10:;

    /* "View.MemoryView":1262
 *             order = get_best_order(&dst, ndim)
 * 
 *         tmpdata = copy_data_to_temp(&src, &tmp, order, ndim)             # <<<<<<<<<<<<<<
 *         src = tmp
 * 
 */
    __pyx_t_6 = __pyx_memoryview_copy_data_to_temp((&__pyx_v_src), (&__pyx_v_tmp), __pyx_v_order, __pyx_v_ndim); if (unlikely(__pyx_t_6 == NULL)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1262; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
    __pyx_v_tmpdata = __pyx_t_6;

    /* "View.MemoryView":1263
 * 
 *         tmpdata = copy_data_to_temp(&src, &tmp, order, ndim)
 *         src = tmp             # <<<<<<<<<<<<<<
 * 
 *     if not broadcasting:
 */
    __pyx_v_src = __pyx_v_tmp;
    goto __pyx_L9;
  }
  __pyx_L9:;

  /* "View.MemoryView":1265
 *         src = tmp
 * 
 *     if not broadcasting:             # <<<<<<<<<<<<<<
 * 
 * 
 */
  __pyx_t_2 = ((!(__pyx_v_broadcasting != 0)) != 0);
  if (__pyx_t_2) {

    /* "View.MemoryView":1268
 * 
 * 
 *         if slice_is_contig(&src, 'C', ndim):             # <<<<<<<<<<<<<<
 *             direct_copy = slice_is_contig(&dst, 'C', ndim)
 *         elif slice_is_contig(&src, 'F', ndim):
 */
    __pyx_t_2 = (__pyx_memviewslice_is_contig((&__pyx_v_src), 'C', __pyx_v_ndim) != 0);
    if (__pyx_t_2) {

      /* "View.MemoryView":1269
 * 
 *         if slice_is_contig(&src, 'C', ndim):
 *             direct_copy = slice_is_contig(&dst, 'C', ndim)             # <<<<<<<<<<<<<<
 *         elif slice_is_contig(&src, 'F', ndim):
 *             direct_copy = slice_is_contig(&dst, 'F', ndim)
 */
      __pyx_v_direct_copy = __pyx_memviewslice_is_contig((&__pyx_v_dst), 'C', __pyx_v_ndim);
      goto __pyx_L12;
    }

    /* "View.MemoryView":1270
 *         if slice_is_contig(&src, 'C', ndim):
 *             direct_copy = slice_is_contig(&dst, 'C', ndim)
 *         elif slice_is_contig(&src, 'F', ndim):             # <<<<<<<<<<<<<<
 *             direct_copy = slice_is_contig(&dst, 'F', ndim)
 * 
 */
    __pyx_t_2 = (__pyx_memviewslice_is_contig((&__pyx_v_src), 'F', __pyx_v_ndim) != 0);
    if (__pyx_t_2) {

      /* "View.MemoryView":1271
 *             direct_copy = slice_is_contig(&dst, 'C', ndim)
 *         elif slice_is_contig(&src, 'F', ndim):
 *             direct_copy = slice_is_contig(&dst, 'F', ndim)             # <<<<<<<<<<<<<<
 * 
 *         if direct_copy:
 */
      __pyx_v_direct_copy = __pyx_memviewslice_is_contig((&__pyx_v_dst), 'F', __pyx_v_ndim);
      goto __pyx_L12;
    }
    __pyx_L12:;

    /* "View.MemoryView":1273
 *             direct_copy = slice_is_contig(&dst, 'F', ndim)
 * 
 *         if direct_copy:             # <<<<<<<<<<<<<<
 * 
 *             refcount_copying(&dst, dtype_is_object, ndim, False)
 */
    __pyx_t_2 = (__pyx_v_direct_copy != 0);
    if (__pyx_t_2) {

      /* "View.MemoryView":1275
 *         if direct_copy:
 * 
 *             refcount_copying(&dst, dtype_is_object, ndim, False)             # <<<<<<<<<<<<<<
 *             memcpy(dst.data, src.data, slice_get_size(&src, ndim))
 *             refcount_copying(&dst, dtype_is_object, ndim, True)
 */
      __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 0);

      /* "View.MemoryView":1276
 * 
 *             refcount_copying(&dst, dtype_is_object, ndim, False)
 *             memcpy(dst.data, src.data, slice_get_size(&src, ndim))             # <<<<<<<<<<<<<<
 *             refcount_copying(&dst, dtype_is_object, ndim, True)
 *             free(tmpdata)
 */
      memcpy(__pyx_v_dst.data, __pyx_v_src.data, __pyx_memoryview_slice_get_size((&__pyx_v_src), __pyx_v_ndim));

      /* "View.MemoryView":1277
 *             refcount_copying(&dst, dtype_is_object, ndim, False)
 *             memcpy(dst.data, src.data, slice_get_size(&src, ndim))
 *             refcount_copying(&dst, dtype_is_object, ndim, True)             # <<<<<<<<<<<<<<
 *             free(tmpdata)
 *             return 0
 */
      __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 1);

      /* "View.MemoryView":1278
 *             memcpy(dst.data, src.data, slice_get_size(&src, ndim))
 *             refcount_copying(&dst, dtype_is_object, ndim, True)
 *             free(tmpdata)             # <<<<<<<<<<<<<<
 *             return 0
 * 
 */
      free(__pyx_v_tmpdata);

      /* "View.MemoryView":1279
 *             refcount_copying(&dst, dtype_is_object, ndim, True)
 *             free(tmpdata)
 *             return 0             # <<<<<<<<<<<<<<
 * 
 *     if order == 'F' == get_best_order(&dst, ndim):
 */
      __pyx_r = 0;
      goto __pyx_L0;
    }
    goto __pyx_L11;
  }
  __pyx_L11:;

  /* "View.MemoryView":1281
 *             return 0
 * 
 *     if order == 'F' == get_best_order(&dst, ndim):             # <<<<<<<<<<<<<<
 * 
 * 
 */
  __pyx_t_2 = (__pyx_v_order == 'F');
  if (__pyx_t_2) {
    __pyx_t_2 = ('F' == __pyx_get_best_slice_order((&__pyx_v_dst), __pyx_v_ndim));
  }
  __pyx_t_7 = (__pyx_t_2 != 0);
  if (__pyx_t_7) {

    /* "View.MemoryView":1284
 * 
 * 
 *         transpose_memslice(&src)             # <<<<<<<<<<<<<<
 *         transpose_memslice(&dst)
 * 
 */
    __pyx_t_5 = __pyx_memslice_transpose((&__pyx_v_src)); if (unlikely(__pyx_t_5 == 0)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1284; __pyx_clineno = __LINE__; goto __pyx_L1_error;}

    /* "View.MemoryView":1285
 * 
 *         transpose_memslice(&src)
 *         transpose_memslice(&dst)             # <<<<<<<<<<<<<<
 * 
 *     refcount_copying(&dst, dtype_is_object, ndim, False)
 */
    __pyx_t_5 = __pyx_memslice_transpose((&__pyx_v_dst)); if (unlikely(__pyx_t_5 == 0)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 1285; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
    goto __pyx_L14;
  }
  __pyx_L14:;

  /* "View.MemoryView":1287
 *         transpose_memslice(&dst)
 * 
 *     refcount_copying(&dst, dtype_is_object, ndim, False)             # <<<<<<<<<<<<<<
 *     copy_strided_to_strided(&src, &dst, ndim, itemsize)
 *     refcount_copying(&dst, dtype_is_object, ndim, True)
 */
  __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 0);

  /* "View.MemoryView":1288
 * 
 *     refcount_copying(&dst, dtype_is_object, ndim, False)
 *     copy_strided_to_strided(&src, &dst, ndim, itemsize)             # <<<<<<<<<<<<<<
 *     refcount_copying(&dst, dtype_is_object, ndim, True)
 * 
 */
  copy_strided_to_strided((&__pyx_v_src), (&__pyx_v_dst), __pyx_v_ndim, __pyx_v_itemsize);

  /* "View.MemoryView":1289
 *     refcount_copying(&dst, dtype_is_object, ndim, False)
 *     copy_strided_to_strided(&src, &dst, ndim, itemsize)
 *     refcount_copying(&dst, dtype_is_object, ndim, True)             # <<<<<<<<<<<<<<
 * 
 *     free(tmpdata)
 */
  __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 1);

  /* "View.MemoryView":1291
 *     refcount_copying(&dst, dtype_is_object, ndim, True)
 * 
 *     free(tmpdata)             # <<<<<<<<<<<<<<
 *     return 0
 * 
 */
  free(__pyx_v_tmpdata);

  /* "View.MemoryView":1292
 * 
 *     free(tmpdata)
 *     return 0             # <<<<<<<<<<<<<<
 * 
 * @cname('__pyx_memoryview_broadcast_leading')
 */
  __pyx_r = 0;
  goto __pyx_L0;

  /* "View.MemoryView":1223
 * 
 * @cname('__pyx_memoryview_copy_contents')
 * cdef int memoryview_copy_contents(__Pyx_memviewslice src,             # <<<<<<<<<<<<<<
 *                                   __Pyx_memviewslice dst,
 *                                   int src_ndim, int dst_ndim,
 */

  /* function exit code */
  __pyx_L1_error:;
  {
    #ifdef WITH_THREAD
    PyGILState_STATE __pyx_gilstate_save = PyGILState_Ensure();
    #endif
    __Pyx_AddTraceback("View.MemoryView.memoryview_copy_contents", __pyx_clineno, __pyx_lineno, __pyx_filename);
    #ifdef WITH_THREAD
    PyGILState_Release(__pyx_gilstate_save);
    #endif
  }
  __pyx_r = -1;
  __pyx_L0:;
  return __pyx_r;
}

/* "View.MemoryView":1295
 * 
 * @cname('__pyx_memoryview_broadcast_leading')
 * cdef void broadcast_leading(__Pyx_memviewslice *mslice,             # <<<<<<<<<<<<<<
 *                             int ndim,
 *                             int ndim_other) nogil:
 */

static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *__pyx_v_mslice, int __pyx_v_ndim, int __pyx_v_ndim_other) {
  int __pyx_v_i;
  int __pyx_v_offset;
  int __pyx_t_1;
  int __pyx_t_2;

  /* "View.MemoryView":1299
 *                             int ndim_other) nogil:
 *     cdef int i
 *     cdef int offset = ndim_other - ndim             # <<<<<<<<<<<<<<
 * 
 *     for i in range(ndim - 1, -1, -1):
 */
  __pyx_v_offset = (__pyx_v_ndim_other - __pyx_v_ndim);

  /* "View.MemoryView":1301
 *     cdef int offset = ndim_other - ndim
 * 
 *     for i in range(ndim - 1, -1, -1):             # <<<<<<<<<<<<<<
 *         mslice.shape[i + offset] = mslice.shape[i]
 *         mslice.strides[i + offset] = mslice.strides[i]
 */
  for (__pyx_t_1 = (__pyx_v_ndim - 1); __pyx_t_1 > -1; __pyx_t_1-=1) {
    __pyx_v_i = __pyx_t_1;

    /* "View.MemoryView":1302
 * 
 *     for i in range(ndim - 1, -1, -1):
 *         mslice.shape[i + offset] = mslice.shape[i]             # <<<<<<<<<<<<<<
 *         mslice.strides[i + offset] = mslice.strides[i]
 *         mslice.suboffsets[i + offset] = mslice.suboffsets[i]
 */
    (__pyx_v_mslice->shape[(__pyx_v_i + __pyx_v_offset)]) = (__pyx_v_mslice->shape[__pyx_v_i]);

    /* "View.MemoryView":1303
 *     for i in range(ndim - 1, -1, -1):
 *         mslice.shape[i + offset] = mslice.shape[i]
 *         mslice.strides[i + offset] = mslice.strides[i]             # <<<<<<<<<<<<<<
 *         mslice.suboffsets[i + offset] = mslice.suboffsets[i]
 * 
 */
    (__pyx_v_mslice->strides[(__pyx_v_i + __pyx_v_offset)]) = (__pyx_v_mslice->strides[__pyx_v_i]);

    /* "View.MemoryView":1304
 *         mslice.shape[i + offset] = mslice.shape[i]
 *         mslice.strides[i + offset] = mslice.strides[i]
 *         mslice.suboffsets[i + offset] = mslice.suboffsets[i]             # <<<<<<<<<<<<<<
 * 
 *     for i in range(offset):
 */
    (__pyx_v_mslice->suboffsets[(__pyx_v_i + __pyx_v_offset)]) = (__pyx_v_mslice->suboffsets[__pyx_v_i]);
  }

  /* "View.MemoryView":1306
 *         mslice.suboffsets[i + offset] = mslice.suboffsets[i]
 * 
 *     for i in range(offset):             # <<<<<<<<<<<<<<
 *         mslice.shape[i] = 1
 *         mslice.strides[i] = mslice.strides[0]
 */
  __pyx_t_1 = __pyx_v_offset;
  for (__pyx_t_2 = 0; __pyx_t_2 < __pyx_t_1; __pyx_t_2+=1) {
    __pyx_v_i = __pyx_t_2;

    /* "View.MemoryView":1307
 * 
 *     for i in range(offset):
 *         mslice.shape[i] = 1             # <<<<<<<<<<<<<<
 *         mslice.strides[i] = mslice.strides[0]
 *         mslice.suboffsets[i] = -1
 */
    (__pyx_v_mslice->shape[__pyx_v_i]) = 1;

    /* "View.MemoryView":1308
 *     for i in range(offset):
 *         mslice.shape[i] = 1
 *         mslice.strides[i] = mslice.strides[0]             # <<<<<<<<<<<<<<
 *         mslice.suboffsets[i] = -1
 * 
 */
    (__pyx_v_mslice->strides[__pyx_v_i]) = (__pyx_v_mslice->strides[0]);

    /* "View.MemoryView":1309
 *         mslice.shape[i] = 1
 *         mslice.strides[i] = mslice.strides[0]
 *         mslice.suboffsets[i] = -1             # <<<<<<<<<<<<<<
 * 
 * 
 */
    (__pyx_v_mslice->suboffsets[__pyx_v_i]) = -1;
  }

  /* "View.MemoryView":1295
 * 
 * @cname('__pyx_memoryview_broadcast_leading')
 * cdef void broadcast_leading(__Pyx_memviewslice *mslice,             # <<<<<<<<<<<<<<
 *                             int ndim,
 *                             int ndim_other) nogil:
 */

  /* function exit code */
}

/* "View.MemoryView":1317
 * 
 * @cname('__pyx_memoryview_refcount_copying')
 * cdef void refcount_copying(__Pyx_memviewslice *dst, bint dtype_is_object,             # <<<<<<<<<<<<<<
 *                            int ndim, bint inc) nogil:
 * 
 */

static void __pyx_memoryview_refcount_copying(__Pyx_memviewslice *__pyx_v_dst, int __pyx_v_dtype_is_object, int __pyx_v_ndim, int __pyx_v_inc) {
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/* "View.MemoryView":1326
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/* "View.MemoryView":1352
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static void __pyx_memoryview_slice_assign_scalar(__Pyx_memviewslice *__pyx_v_dst, int __pyx_v_ndim, size_t __pyx_v_itemsize, void *__pyx_v_item, int __pyx_v_dtype_is_object) {

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 * 
 */
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  /* function exit code */
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/* "View.MemoryView":1362
 * 
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static void __pyx_memoryview__slice_assign_scalar(char *__pyx_v_data, Py_ssize_t *__pyx_v_shape, Py_ssize_t *__pyx_v_strides, int __pyx_v_ndim, size_t __pyx_v_itemsize, void *__pyx_v_item) {
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  /* "View.MemoryView":1366
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 *     cdef Py_ssize_t extent = shape[0]
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 */
  __pyx_v_stride = (__pyx_v_strides[0]);

  /* "View.MemoryView":1367
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  /* "View.MemoryView":1369
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  __pyx_t_1 = ((__pyx_v_ndim == 1) != 0);
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    /* "View.MemoryView":1370
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    __pyx_t_2 = __pyx_v_extent;
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      /* "View.MemoryView":1371
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      /* "View.MemoryView":1372
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    /* "View.MemoryView":1374
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      /* "View.MemoryView":1375
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  p->obs_intercept.data = NULL;
  p->obs_intercept.memview = NULL;
  p->state_intercept.data = NULL;
  p->state_intercept.memview = NULL;
  p->initial_state.data = NULL;
  p->initial_state.memview = NULL;
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static void __pyx_tp_dealloc_11statsmodels_3tsa_10statespace_11_statespace_sStatespace(PyObject *o) {
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static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_nobs(PyObject *o, CYTHON_UNUSED void *x) {
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}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_k_endog(PyObject *o, CYTHON_UNUSED void *x) {
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}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_k_states(PyObject *o, CYTHON_UNUSED void *x) {
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}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_k_posdef(PyObject *o, CYTHON_UNUSED void *x) {
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}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_obs(PyObject *o, CYTHON_UNUSED void *x) {
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}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_obs_intercept(PyObject *o, CYTHON_UNUSED void *x) {
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static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_state_intercept(PyObject *o, CYTHON_UNUSED void *x) {
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static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_initial_state(PyObject *o, CYTHON_UNUSED void *x) {
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}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_initial_state_cov(PyObject *o, CYTHON_UNUSED void *x) {
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}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_design(PyObject *o, CYTHON_UNUSED void *x) {
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}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_obs_cov(PyObject *o, CYTHON_UNUSED void *x) {
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static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_transition(PyObject *o, CYTHON_UNUSED void *x) {
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}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_selection(PyObject *o, CYTHON_UNUSED void *x) {
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}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_state_cov(PyObject *o, CYTHON_UNUSED void *x) {
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}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_selected_state_cov(PyObject *o, CYTHON_UNUSED void *x) {
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}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_missing(PyObject *o, CYTHON_UNUSED void *x) {
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}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_nmissing(PyObject *o, CYTHON_UNUSED void *x) {
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}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_time_invariant(PyObject *o, CYTHON_UNUSED void *x) {
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}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_initialized(PyObject *o, CYTHON_UNUSED void *x) {
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}

static PyMethodDef __pyx_methods_11statsmodels_3tsa_10statespace_11_statespace_sStatespace[] = {
  {"initialize_known", (PyCFunction)__pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_3initialize_known, METH_VARARGS|METH_KEYWORDS, __pyx_doc_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_2initialize_known},
  {"initialize_approximate_diffuse", (PyCFunction)__pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_5initialize_approximate_diffuse, METH_VARARGS|METH_KEYWORDS, __pyx_doc_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_4initialize_approximate_diffuse},
  {"initialize_stationary", (PyCFunction)__pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_7initialize_stationary, METH_VARARGS|METH_KEYWORDS, __pyx_doc_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_6initialize_stationary},
  {0, 0, 0, 0}
};

static struct PyGetSetDef __pyx_getsets_11statsmodels_3tsa_10statespace_11_statespace_sStatespace[] = {
  {(char *)"nobs", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_nobs, 0, 0, 0},
  {(char *)"k_endog", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_k_endog, 0, 0, 0},
  {(char *)"k_states", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_k_states, 0, 0, 0},
  {(char *)"k_posdef", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_k_posdef, 0, 0, 0},
  {(char *)"obs", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_obs, 0, 0, 0},
  {(char *)"obs_intercept", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_obs_intercept, 0, 0, 0},
  {(char *)"state_intercept", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_state_intercept, 0, 0, 0},
  {(char *)"initial_state", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_initial_state, 0, 0, 0},
  {(char *)"initial_state_cov", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_initial_state_cov, 0, 0, 0},
  {(char *)"design", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_design, 0, 0, 0},
  {(char *)"obs_cov", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_obs_cov, 0, 0, 0},
  {(char *)"transition", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_transition, 0, 0, 0},
  {(char *)"selection", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_selection, 0, 0, 0},
  {(char *)"state_cov", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_state_cov, 0, 0, 0},
  {(char *)"selected_state_cov", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_selected_state_cov, 0, 0, 0},
  {(char *)"missing", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_missing, 0, 0, 0},
  {(char *)"nmissing", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_nmissing, 0, 0, 0},
  {(char *)"time_invariant", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_time_invariant, 0, 0, 0},
  {(char *)"initialized", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_initialized, 0, 0, 0},
  {0, 0, 0, 0, 0}
};

static PyTypeObject __pyx_type_11statsmodels_3tsa_10statespace_11_statespace_sStatespace = {
  PyVarObject_HEAD_INIT(0, 0)
  "statsmodels.tsa.statespace._statespace.sStatespace", /*tp_name*/
  sizeof(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sStatespace), /*tp_basicsize*/
  0, /*tp_itemsize*/
  __pyx_tp_dealloc_11statsmodels_3tsa_10statespace_11_statespace_sStatespace, /*tp_dealloc*/
  0, /*tp_print*/
  0, /*tp_getattr*/
  0, /*tp_setattr*/
  #if PY_MAJOR_VERSION < 3
  0, /*tp_compare*/
  #else
  0, /*reserved*/
  #endif
  0, /*tp_repr*/
  0, /*tp_as_number*/
  0, /*tp_as_sequence*/
  0, /*tp_as_mapping*/
  0, /*tp_hash*/
  0, /*tp_call*/
  0, /*tp_str*/
  0, /*tp_getattro*/
  0, /*tp_setattro*/
  0, /*tp_as_buffer*/
  Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/
  "\n    sStatespace(obs, design, obs_intercept, obs_cov, transition, state_intercept, selection, state_cov)\n\n    *See Durbin and Koopman (2012), Chapter 4 for all notation*\n    ", /*tp_doc*/
  0, /*tp_traverse*/
  0, /*tp_clear*/
  0, /*tp_richcompare*/
  0, /*tp_weaklistoffset*/
  0, /*tp_iter*/
  0, /*tp_iternext*/
  __pyx_methods_11statsmodels_3tsa_10statespace_11_statespace_sStatespace, /*tp_methods*/
  0, /*tp_members*/
  __pyx_getsets_11statsmodels_3tsa_10statespace_11_statespace_sStatespace, /*tp_getset*/
  0, /*tp_base*/
  0, /*tp_dict*/
  0, /*tp_descr_get*/
  0, /*tp_descr_set*/
  0, /*tp_dictoffset*/
  __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11sStatespace_1__init__, /*tp_init*/
  0, /*tp_alloc*/
  __pyx_tp_new_11statsmodels_3tsa_10statespace_11_statespace_sStatespace, /*tp_new*/
  0, /*tp_free*/
  0, /*tp_is_gc*/
  0, /*tp_bases*/
  0, /*tp_mro*/
  0, /*tp_cache*/
  0, /*tp_subclasses*/
  0, /*tp_weaklist*/
  0, /*tp_del*/
  0, /*tp_version_tag*/
  #if PY_VERSION_HEX >= 0x030400a1
  0, /*tp_finalize*/
  #endif
};
static struct __pyx_vtabstruct_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter __pyx_vtable_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter;

static PyObject *__pyx_tp_new_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
  struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *p;
  PyObject *o;
  if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
    o = (*t->tp_alloc)(t, 0);
  } else {
    o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
  }
  if (unlikely(!o)) return 0;
  p = ((struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *)o);
  p->__pyx_vtab = __pyx_vtabptr_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter;
  p->model = ((struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sStatespace *)Py_None); Py_INCREF(Py_None);
  p->loglikelihood.data = NULL;
  p->loglikelihood.memview = NULL;
  p->filtered_state.data = NULL;
  p->filtered_state.memview = NULL;
  p->predicted_state.data = NULL;
  p->predicted_state.memview = NULL;
  p->forecast.data = NULL;
  p->forecast.memview = NULL;
  p->forecast_error.data = NULL;
  p->forecast_error.memview = NULL;
  p->filtered_state_cov.data = NULL;
  p->filtered_state_cov.memview = NULL;
  p->predicted_state_cov.data = NULL;
  p->predicted_state_cov.memview = NULL;
  p->forecast_error_cov.data = NULL;
  p->forecast_error_cov.memview = NULL;
  p->converged_forecast_error_cov.data = NULL;
  p->converged_forecast_error_cov.memview = NULL;
  p->converged_filtered_state_cov.data = NULL;
  p->converged_filtered_state_cov.memview = NULL;
  p->converged_predicted_state_cov.data = NULL;
  p->converged_predicted_state_cov.memview = NULL;
  p->selected_obs.data = NULL;
  p->selected_obs.memview = NULL;
  p->selected_design.data = NULL;
  p->selected_design.memview = NULL;
  p->selected_obs_cov.data = NULL;
  p->selected_obs_cov.memview = NULL;
  p->forecast_error_fac.data = NULL;
  p->forecast_error_fac.memview = NULL;
  p->forecast_error_ipiv.data = NULL;
  p->forecast_error_ipiv.memview = NULL;
  p->forecast_error_work.data = NULL;
  p->forecast_error_work.memview = NULL;
  p->tmp0.data = NULL;
  p->tmp0.memview = NULL;
  p->tmp1.data = NULL;
  p->tmp1.memview = NULL;
  p->tmp3.data = NULL;
  p->tmp3.memview = NULL;
  p->tmp2.data = NULL;
  p->tmp2.memview = NULL;
  return o;
}

static void __pyx_tp_dealloc_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter(PyObject *o) {
  struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *p = (struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *)o;
  #if PY_VERSION_HEX >= 0x030400a1
  if (unlikely(Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
    if (PyObject_CallFinalizerFromDealloc(o)) return;
  }
  #endif
  PyObject_GC_UnTrack(o);
  Py_CLEAR(p->model);
  __PYX_XDEC_MEMVIEW(&p->loglikelihood, 1);
  __PYX_XDEC_MEMVIEW(&p->filtered_state, 1);
  __PYX_XDEC_MEMVIEW(&p->predicted_state, 1);
  __PYX_XDEC_MEMVIEW(&p->forecast, 1);
  __PYX_XDEC_MEMVIEW(&p->forecast_error, 1);
  __PYX_XDEC_MEMVIEW(&p->filtered_state_cov, 1);
  __PYX_XDEC_MEMVIEW(&p->predicted_state_cov, 1);
  __PYX_XDEC_MEMVIEW(&p->forecast_error_cov, 1);
  __PYX_XDEC_MEMVIEW(&p->converged_forecast_error_cov, 1);
  __PYX_XDEC_MEMVIEW(&p->converged_filtered_state_cov, 1);
  __PYX_XDEC_MEMVIEW(&p->converged_predicted_state_cov, 1);
  __PYX_XDEC_MEMVIEW(&p->selected_obs, 1);
  __PYX_XDEC_MEMVIEW(&p->selected_design, 1);
  __PYX_XDEC_MEMVIEW(&p->selected_obs_cov, 1);
  __PYX_XDEC_MEMVIEW(&p->forecast_error_fac, 1);
  __PYX_XDEC_MEMVIEW(&p->forecast_error_ipiv, 1);
  __PYX_XDEC_MEMVIEW(&p->forecast_error_work, 1);
  __PYX_XDEC_MEMVIEW(&p->tmp0, 1);
  __PYX_XDEC_MEMVIEW(&p->tmp1, 1);
  __PYX_XDEC_MEMVIEW(&p->tmp3, 1);
  __PYX_XDEC_MEMVIEW(&p->tmp2, 1);
  (*Py_TYPE(o)->tp_free)(o);
}

static int __pyx_tp_traverse_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter(PyObject *o, visitproc v, void *a) {
  int e;
  struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *p = (struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *)o;
  if (p->model) {
    e = (*v)(((PyObject*)p->model), a); if (e) return e;
  }
  return 0;
}

static int __pyx_tp_clear_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter(PyObject *o) {
  PyObject* tmp;
  struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *p = (struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter *)o;
  tmp = ((PyObject*)p->model);
  p->model = ((struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sStatespace *)Py_None); Py_INCREF(Py_None);
  Py_XDECREF(tmp);
  return 0;
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_model(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_5model_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_t(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_1t_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_tolerance(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_9tolerance_1__get__(o);
}

static int __pyx_setprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_tolerance(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
  if (v) {
    return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_9tolerance_3__set__(o, v);
  }
  else {
    PyErr_SetString(PyExc_NotImplementedError, "__del__");
    return -1;
  }
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_converged(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_9converged_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_period_converged(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_16period_converged_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_time_invariant(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_14time_invariant_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_filter_method(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_13filter_method_1__get__(o);
}

static int __pyx_setprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_filter_method(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
  if (v) {
    return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_13filter_method_3__set__(o, v);
  }
  else {
    PyErr_SetString(PyExc_NotImplementedError, "__del__");
    return -1;
  }
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_inversion_method(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_16inversion_method_1__get__(o);
}

static int __pyx_setprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_inversion_method(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
  if (v) {
    return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_16inversion_method_3__set__(o, v);
  }
  else {
    PyErr_SetString(PyExc_NotImplementedError, "__del__");
    return -1;
  }
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_stability_method(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_16stability_method_1__get__(o);
}

static int __pyx_setprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_stability_method(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
  if (v) {
    return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_16stability_method_3__set__(o, v);
  }
  else {
    PyErr_SetString(PyExc_NotImplementedError, "__del__");
    return -1;
  }
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_conserve_memory(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_15conserve_memory_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_loglikelihood_burn(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_18loglikelihood_burn_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_loglikelihood(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_13loglikelihood_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_filtered_state(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_14filtered_state_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_predicted_state(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_15predicted_state_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_forecast(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_8forecast_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_forecast_error(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_14forecast_error_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_filtered_state_cov(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_18filtered_state_cov_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_predicted_state_cov(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_19predicted_state_cov_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_forecast_error_cov(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_18forecast_error_cov_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_converged_forecast_error_cov(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_28converged_forecast_error_cov_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_converged_filtered_state_cov(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_28converged_filtered_state_cov_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_converged_predicted_state_cov(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_29converged_predicted_state_cov_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_converged_determinant(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_21converged_determinant_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_selected_obs(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_12selected_obs_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_selected_design(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_15selected_design_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_selected_obs_cov(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_16selected_obs_cov_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_forecast_error_fac(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_18forecast_error_fac_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_forecast_error_ipiv(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_19forecast_error_ipiv_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_forecast_error_work(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_19forecast_error_work_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_tmp0(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_4tmp0_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_tmp1(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_4tmp1_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_tmp3(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_4tmp3_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_tmp2(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_4tmp2_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_determinant(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_11determinant_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_k_endog(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_7k_endog_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_k_states(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_8k_states_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_k_posdef(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_8k_posdef_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_k_endog2(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_8k_endog2_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_k_states2(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_9k_states2_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_k_endogstates(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_13k_endogstates_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_ldwork(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_6ldwork_1__get__(o);
}

static PyMethodDef __pyx_methods_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter[] = {
  {"set_filter_method", (PyCFunction)__pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_3set_filter_method, METH_VARARGS|METH_KEYWORDS, __pyx_doc_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_2set_filter_method},
  {"seek", (PyCFunction)__pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_5seek, METH_VARARGS|METH_KEYWORDS, __pyx_doc_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_4seek},
  {"__next__", (PyCFunction)__pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_11__next__, METH_NOARGS|METH_COEXIST, __pyx_doc_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_10__next__},
  {"initialize_statespace_object_pointers", (PyCFunction)__pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_13initialize_statespace_object_pointers, METH_NOARGS, 0},
  {"initialize_filter_object_pointers", (PyCFunction)__pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_15initialize_filter_object_pointers, METH_NOARGS, 0},
  {"select_missing", (PyCFunction)__pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_17select_missing, METH_NOARGS, 0},
  {0, 0, 0, 0}
};

static struct PyGetSetDef __pyx_getsets_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter[] = {
  {(char *)"model", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_model, 0, 0, 0},
  {(char *)"t", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_t, 0, 0, 0},
  {(char *)"tolerance", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_tolerance, __pyx_setprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_tolerance, 0, 0},
  {(char *)"converged", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_converged, 0, 0, 0},
  {(char *)"period_converged", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_period_converged, 0, 0, 0},
  {(char *)"time_invariant", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_time_invariant, 0, 0, 0},
  {(char *)"filter_method", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_filter_method, __pyx_setprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_filter_method, 0, 0},
  {(char *)"inversion_method", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_inversion_method, __pyx_setprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_inversion_method, 0, 0},
  {(char *)"stability_method", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_stability_method, __pyx_setprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_stability_method, 0, 0},
  {(char *)"conserve_memory", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_conserve_memory, 0, 0, 0},
  {(char *)"loglikelihood_burn", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_loglikelihood_burn, 0, 0, 0},
  {(char *)"loglikelihood", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_loglikelihood, 0, 0, 0},
  {(char *)"filtered_state", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_filtered_state, 0, 0, 0},
  {(char *)"predicted_state", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_predicted_state, 0, 0, 0},
  {(char *)"forecast", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_forecast, 0, 0, 0},
  {(char *)"forecast_error", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_forecast_error, 0, 0, 0},
  {(char *)"filtered_state_cov", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_filtered_state_cov, 0, 0, 0},
  {(char *)"predicted_state_cov", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_predicted_state_cov, 0, 0, 0},
  {(char *)"forecast_error_cov", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_forecast_error_cov, 0, 0, 0},
  {(char *)"converged_forecast_error_cov", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_converged_forecast_error_cov, 0, 0, 0},
  {(char *)"converged_filtered_state_cov", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_converged_filtered_state_cov, 0, 0, 0},
  {(char *)"converged_predicted_state_cov", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_converged_predicted_state_cov, 0, 0, 0},
  {(char *)"converged_determinant", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_converged_determinant, 0, 0, 0},
  {(char *)"selected_obs", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_selected_obs, 0, 0, 0},
  {(char *)"selected_design", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_selected_design, 0, 0, 0},
  {(char *)"selected_obs_cov", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_selected_obs_cov, 0, 0, 0},
  {(char *)"forecast_error_fac", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_forecast_error_fac, 0, 0, 0},
  {(char *)"forecast_error_ipiv", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_forecast_error_ipiv, 0, 0, 0},
  {(char *)"forecast_error_work", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_forecast_error_work, 0, 0, 0},
  {(char *)"tmp0", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_tmp0, 0, 0, 0},
  {(char *)"tmp1", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_tmp1, 0, 0, 0},
  {(char *)"tmp3", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_tmp3, 0, 0, 0},
  {(char *)"tmp2", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_tmp2, 0, 0, 0},
  {(char *)"determinant", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_determinant, 0, 0, 0},
  {(char *)"k_endog", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_k_endog, 0, 0, 0},
  {(char *)"k_states", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_k_states, 0, 0, 0},
  {(char *)"k_posdef", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_k_posdef, 0, 0, 0},
  {(char *)"k_endog2", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_k_endog2, 0, 0, 0},
  {(char *)"k_states2", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_k_states2, 0, 0, 0},
  {(char *)"k_endogstates", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_k_endogstates, 0, 0, 0},
  {(char *)"ldwork", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_ldwork, 0, 0, 0},
  {0, 0, 0, 0, 0}
};

static PyTypeObject __pyx_type_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter = {
  PyVarObject_HEAD_INIT(0, 0)
  "statsmodels.tsa.statespace._statespace.sKalmanFilter", /*tp_name*/
  sizeof(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter), /*tp_basicsize*/
  0, /*tp_itemsize*/
  __pyx_tp_dealloc_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter, /*tp_dealloc*/
  0, /*tp_print*/
  0, /*tp_getattr*/
  0, /*tp_setattr*/
  #if PY_MAJOR_VERSION < 3
  0, /*tp_compare*/
  #else
  0, /*reserved*/
  #endif
  0, /*tp_repr*/
  0, /*tp_as_number*/
  0, /*tp_as_sequence*/
  0, /*tp_as_mapping*/
  0, /*tp_hash*/
  __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_9__call__, /*tp_call*/
  0, /*tp_str*/
  0, /*tp_getattro*/
  0, /*tp_setattro*/
  0, /*tp_as_buffer*/
  Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
  "\n    sKalmanFilter(model, filter=FILTER_CONVENTIONAL, inversion_method=INVERT_UNIVARIATE | SOLVE_CHOLESKY, stability_method=STABILITY_FORCE_SYMMETRY, tolerance=1e-19)\n\n    A representation of the Kalman filter recursions.\n\n    While the filter is mathematically represented as a recursion, it is here\n    translated into Python as a stateful iterator.\n\n    Because there are actually several types of Kalman filter depending on the\n    state space model of interest, this class only handles the *iteration*\n    aspect of filtering, and delegates the actual operations to four general\n    workhorse routines, which can be implemented separately for each type of\n    Kalman filter.\n\n    In order to maintain a consistent interface, and because these four general\n    routines may be quite different across filter types, their argument is only\n    the stateful ?KalmanFilter object. Furthermore, in order to allow the\n    different types of filter to substitute alternate matrices, this class\n    defines a set of pointers to the various state space arrays and the\n    filtering output arrays.\n\n    For example, handling missing observations requires not only substituting\n    `obs`, `design`, and `obs_cov` matrices, but the new matrices actually have\n    different dimensions than the originals. This can be flexibly accomodated\n    simply by replacing e.g. the `obs` pointer to the substituted `obs` array\n    and replacing `k_endog` for that iteration. Then in the next iteration, when\n    the `obs` vector may be missing different elements (or none at all), it can\n    again be redefined.\n\n    Each iteration of the filter (see `__next__`) proceeds in a number of\n    steps.\n\n    `initialize_object_pointers` initializes pointers to current-iteration\n    objects (i.e. the state space arrays and filter output arrays).  \n\n    `initialize_function_pointers` initializes pointers to the appropriate\n    Kalman filtering routines (i.e. `forecast_conventional` or\n    `forecast_exact_initial`, etc.).  \n\n    `select_arrays` converts the base arrays into \"selected\" arrays using\n    selection matrices. In particular, it handles the state covariance matrix\n    and redefined matrices based on missing values.  \n\n    `post_convergence` handles copying arrays from time $t-1$ to time $t$ when\n    the Kalman filter has converged and they don't need to be re-calculated.  \n\n    `forecasting` calls the Kalman filter `forcasting_<filter type>` routine\n\n    `inversion` calls the appropriate function to invert the forecast error\n    covariance matrix.  \n\n    `updating` calls the Kalman filter `updating_<filter type>` routine\n\n    `loglikelihood` calls the Kalman filter `loglikelihood_<filter type>` routine\n\n    `prediction` calls the Kalman filter `prediction_<filter type>` routine\n\n    `numerical_stability` performs end-of-iteration tasks to improve the numerical\n    stability of the filter \n\n    `check_convergence` checks for convergence of the filter to steady-state.\n    ", /*tp_doc*/
  __pyx_tp_traverse_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter, /*tp_traverse*/
  __pyx_tp_clear_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter, /*tp_clear*/
  0, /*tp_richcompare*/
  0, /*tp_weaklistoffset*/
  __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_7__iter__, /*tp_iter*/
  __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_11__next__, /*tp_iternext*/
  __pyx_methods_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter, /*tp_methods*/
  0, /*tp_members*/
  __pyx_getsets_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter, /*tp_getset*/
  0, /*tp_base*/
  0, /*tp_dict*/
  0, /*tp_descr_get*/
  0, /*tp_descr_set*/
  0, /*tp_dictoffset*/
  __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13sKalmanFilter_1__init__, /*tp_init*/
  0, /*tp_alloc*/
  __pyx_tp_new_11statsmodels_3tsa_10statespace_11_statespace_sKalmanFilter, /*tp_new*/
  0, /*tp_free*/
  0, /*tp_is_gc*/
  0, /*tp_bases*/
  0, /*tp_mro*/
  0, /*tp_cache*/
  0, /*tp_subclasses*/
  0, /*tp_weaklist*/
  0, /*tp_del*/
  0, /*tp_version_tag*/
  #if PY_VERSION_HEX >= 0x030400a1
  0, /*tp_finalize*/
  #endif
};

static PyObject *__pyx_tp_new_11statsmodels_3tsa_10statespace_11_statespace_zStatespace(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
  struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zStatespace *p;
  PyObject *o;
  if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
    o = (*t->tp_alloc)(t, 0);
  } else {
    o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
  }
  if (unlikely(!o)) return 0;
  p = ((struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zStatespace *)o);
  p->obs.data = NULL;
  p->obs.memview = NULL;
  p->obs_intercept.data = NULL;
  p->obs_intercept.memview = NULL;
  p->state_intercept.data = NULL;
  p->state_intercept.memview = NULL;
  p->initial_state.data = NULL;
  p->initial_state.memview = NULL;
  p->initial_state_cov.data = NULL;
  p->initial_state_cov.memview = NULL;
  p->design.data = NULL;
  p->design.memview = NULL;
  p->obs_cov.data = NULL;
  p->obs_cov.memview = NULL;
  p->transition.data = NULL;
  p->transition.memview = NULL;
  p->selection.data = NULL;
  p->selection.memview = NULL;
  p->state_cov.data = NULL;
  p->state_cov.memview = NULL;
  p->selected_state_cov.data = NULL;
  p->selected_state_cov.memview = NULL;
  p->missing.data = NULL;
  p->missing.memview = NULL;
  p->nmissing.data = NULL;
  p->nmissing.memview = NULL;
  p->tmp.data = NULL;
  p->tmp.memview = NULL;
  return o;
}

static void __pyx_tp_dealloc_11statsmodels_3tsa_10statespace_11_statespace_zStatespace(PyObject *o) {
  struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zStatespace *p = (struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zStatespace *)o;
  #if PY_VERSION_HEX >= 0x030400a1
  if (unlikely(Py_TYPE(o)->tp_finalize) && (!PyType_IS_GC(Py_TYPE(o)) || !_PyGC_FINALIZED(o))) {
    if (PyObject_CallFinalizerFromDealloc(o)) return;
  }
  #endif
  __PYX_XDEC_MEMVIEW(&p->obs, 1);
  __PYX_XDEC_MEMVIEW(&p->obs_intercept, 1);
  __PYX_XDEC_MEMVIEW(&p->state_intercept, 1);
  __PYX_XDEC_MEMVIEW(&p->initial_state, 1);
  __PYX_XDEC_MEMVIEW(&p->initial_state_cov, 1);
  __PYX_XDEC_MEMVIEW(&p->design, 1);
  __PYX_XDEC_MEMVIEW(&p->obs_cov, 1);
  __PYX_XDEC_MEMVIEW(&p->transition, 1);
  __PYX_XDEC_MEMVIEW(&p->selection, 1);
  __PYX_XDEC_MEMVIEW(&p->state_cov, 1);
  __PYX_XDEC_MEMVIEW(&p->selected_state_cov, 1);
  __PYX_XDEC_MEMVIEW(&p->missing, 1);
  __PYX_XDEC_MEMVIEW(&p->nmissing, 1);
  __PYX_XDEC_MEMVIEW(&p->tmp, 1);
  (*Py_TYPE(o)->tp_free)(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_nobs(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_4nobs_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_k_endog(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_7k_endog_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_k_states(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_8k_states_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_k_posdef(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_8k_posdef_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_obs(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_3obs_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_obs_intercept(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_13obs_intercept_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_state_intercept(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_15state_intercept_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_initial_state(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_13initial_state_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_initial_state_cov(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_17initial_state_cov_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_design(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_6design_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_obs_cov(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_7obs_cov_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_transition(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_10transition_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_selection(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_9selection_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_state_cov(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_9state_cov_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_selected_state_cov(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_18selected_state_cov_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_missing(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_7missing_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_nmissing(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_8nmissing_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_time_invariant(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_14time_invariant_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_initialized(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_11initialized_1__get__(o);
}

static PyMethodDef __pyx_methods_11statsmodels_3tsa_10statespace_11_statespace_zStatespace[] = {
  {"initialize_known", (PyCFunction)__pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_3initialize_known, METH_VARARGS|METH_KEYWORDS, __pyx_doc_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_2initialize_known},
  {"initialize_approximate_diffuse", (PyCFunction)__pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_5initialize_approximate_diffuse, METH_VARARGS|METH_KEYWORDS, __pyx_doc_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_4initialize_approximate_diffuse},
  {"initialize_stationary", (PyCFunction)__pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_7initialize_stationary, METH_VARARGS|METH_KEYWORDS, __pyx_doc_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_6initialize_stationary},
  {0, 0, 0, 0}
};

static struct PyGetSetDef __pyx_getsets_11statsmodels_3tsa_10statespace_11_statespace_zStatespace[] = {
  {(char *)"nobs", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_nobs, 0, 0, 0},
  {(char *)"k_endog", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_k_endog, 0, 0, 0},
  {(char *)"k_states", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_k_states, 0, 0, 0},
  {(char *)"k_posdef", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_k_posdef, 0, 0, 0},
  {(char *)"obs", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_obs, 0, 0, 0},
  {(char *)"obs_intercept", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_obs_intercept, 0, 0, 0},
  {(char *)"state_intercept", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_state_intercept, 0, 0, 0},
  {(char *)"initial_state", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_initial_state, 0, 0, 0},
  {(char *)"initial_state_cov", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_initial_state_cov, 0, 0, 0},
  {(char *)"design", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_design, 0, 0, 0},
  {(char *)"obs_cov", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_obs_cov, 0, 0, 0},
  {(char *)"transition", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_transition, 0, 0, 0},
  {(char *)"selection", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_selection, 0, 0, 0},
  {(char *)"state_cov", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_state_cov, 0, 0, 0},
  {(char *)"selected_state_cov", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_selected_state_cov, 0, 0, 0},
  {(char *)"missing", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_missing, 0, 0, 0},
  {(char *)"nmissing", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_nmissing, 0, 0, 0},
  {(char *)"time_invariant", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_time_invariant, 0, 0, 0},
  {(char *)"initialized", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_initialized, 0, 0, 0},
  {0, 0, 0, 0, 0}
};

static PyTypeObject __pyx_type_11statsmodels_3tsa_10statespace_11_statespace_zStatespace = {
  PyVarObject_HEAD_INIT(0, 0)
  "statsmodels.tsa.statespace._statespace.zStatespace", /*tp_name*/
  sizeof(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zStatespace), /*tp_basicsize*/
  0, /*tp_itemsize*/
  __pyx_tp_dealloc_11statsmodels_3tsa_10statespace_11_statespace_zStatespace, /*tp_dealloc*/
  0, /*tp_print*/
  0, /*tp_getattr*/
  0, /*tp_setattr*/
  #if PY_MAJOR_VERSION < 3
  0, /*tp_compare*/
  #else
  0, /*reserved*/
  #endif
  0, /*tp_repr*/
  0, /*tp_as_number*/
  0, /*tp_as_sequence*/
  0, /*tp_as_mapping*/
  0, /*tp_hash*/
  0, /*tp_call*/
  0, /*tp_str*/
  0, /*tp_getattro*/
  0, /*tp_setattro*/
  0, /*tp_as_buffer*/
  Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/
  "\n    zStatespace(obs, design, obs_intercept, obs_cov, transition, state_intercept, selection, state_cov)\n\n    *See Durbin and Koopman (2012), Chapter 4 for all notation*\n    ", /*tp_doc*/
  0, /*tp_traverse*/
  0, /*tp_clear*/
  0, /*tp_richcompare*/
  0, /*tp_weaklistoffset*/
  0, /*tp_iter*/
  0, /*tp_iternext*/
  __pyx_methods_11statsmodels_3tsa_10statespace_11_statespace_zStatespace, /*tp_methods*/
  0, /*tp_members*/
  __pyx_getsets_11statsmodels_3tsa_10statespace_11_statespace_zStatespace, /*tp_getset*/
  0, /*tp_base*/
  0, /*tp_dict*/
  0, /*tp_descr_get*/
  0, /*tp_descr_set*/
  0, /*tp_dictoffset*/
  __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11zStatespace_1__init__, /*tp_init*/
  0, /*tp_alloc*/
  __pyx_tp_new_11statsmodels_3tsa_10statespace_11_statespace_zStatespace, /*tp_new*/
  0, /*tp_free*/
  0, /*tp_is_gc*/
  0, /*tp_bases*/
  0, /*tp_mro*/
  0, /*tp_cache*/
  0, /*tp_subclasses*/
  0, /*tp_weaklist*/
  0, /*tp_del*/
  0, /*tp_version_tag*/
  #if PY_VERSION_HEX >= 0x030400a1
  0, /*tp_finalize*/
  #endif
};
static struct __pyx_vtabstruct_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter __pyx_vtable_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter;

static PyObject *__pyx_tp_new_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
  struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *p;
  PyObject *o;
  if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
    o = (*t->tp_alloc)(t, 0);
  } else {
    o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
  }
  if (unlikely(!o)) return 0;
  p = ((struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *)o);
  p->__pyx_vtab = __pyx_vtabptr_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter;
  p->model = ((struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zStatespace *)Py_None); Py_INCREF(Py_None);
  p->loglikelihood.data = NULL;
  p->loglikelihood.memview = NULL;
  p->filtered_state.data = NULL;
  p->filtered_state.memview = NULL;
  p->predicted_state.data = NULL;
  p->predicted_state.memview = NULL;
  p->forecast.data = NULL;
  p->forecast.memview = NULL;
  p->forecast_error.data = NULL;
  p->forecast_error.memview = NULL;
  p->filtered_state_cov.data = NULL;
  p->filtered_state_cov.memview = NULL;
  p->predicted_state_cov.data = NULL;
  p->predicted_state_cov.memview = NULL;
  p->forecast_error_cov.data = NULL;
  p->forecast_error_cov.memview = NULL;
  p->converged_forecast_error_cov.data = NULL;
  p->converged_forecast_error_cov.memview = NULL;
  p->converged_filtered_state_cov.data = NULL;
  p->converged_filtered_state_cov.memview = NULL;
  p->converged_predicted_state_cov.data = NULL;
  p->converged_predicted_state_cov.memview = NULL;
  p->selected_obs.data = NULL;
  p->selected_obs.memview = NULL;
  p->selected_design.data = NULL;
  p->selected_design.memview = NULL;
  p->selected_obs_cov.data = NULL;
  p->selected_obs_cov.memview = NULL;
  p->forecast_error_fac.data = NULL;
  p->forecast_error_fac.memview = NULL;
  p->forecast_error_ipiv.data = NULL;
  p->forecast_error_ipiv.memview = NULL;
  p->forecast_error_work.data = NULL;
  p->forecast_error_work.memview = NULL;
  p->tmp0.data = NULL;
  p->tmp0.memview = NULL;
  p->tmp1.data = NULL;
  p->tmp1.memview = NULL;
  p->tmp3.data = NULL;
  p->tmp3.memview = NULL;
  p->tmp2.data = NULL;
  p->tmp2.memview = NULL;
  return o;
}

static void __pyx_tp_dealloc_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter(PyObject *o) {
  struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *p = (struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *)o;
  #if PY_VERSION_HEX >= 0x030400a1
  if (unlikely(Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
    if (PyObject_CallFinalizerFromDealloc(o)) return;
  }
  #endif
  PyObject_GC_UnTrack(o);
  Py_CLEAR(p->model);
  __PYX_XDEC_MEMVIEW(&p->loglikelihood, 1);
  __PYX_XDEC_MEMVIEW(&p->filtered_state, 1);
  __PYX_XDEC_MEMVIEW(&p->predicted_state, 1);
  __PYX_XDEC_MEMVIEW(&p->forecast, 1);
  __PYX_XDEC_MEMVIEW(&p->forecast_error, 1);
  __PYX_XDEC_MEMVIEW(&p->filtered_state_cov, 1);
  __PYX_XDEC_MEMVIEW(&p->predicted_state_cov, 1);
  __PYX_XDEC_MEMVIEW(&p->forecast_error_cov, 1);
  __PYX_XDEC_MEMVIEW(&p->converged_forecast_error_cov, 1);
  __PYX_XDEC_MEMVIEW(&p->converged_filtered_state_cov, 1);
  __PYX_XDEC_MEMVIEW(&p->converged_predicted_state_cov, 1);
  __PYX_XDEC_MEMVIEW(&p->selected_obs, 1);
  __PYX_XDEC_MEMVIEW(&p->selected_design, 1);
  __PYX_XDEC_MEMVIEW(&p->selected_obs_cov, 1);
  __PYX_XDEC_MEMVIEW(&p->forecast_error_fac, 1);
  __PYX_XDEC_MEMVIEW(&p->forecast_error_ipiv, 1);
  __PYX_XDEC_MEMVIEW(&p->forecast_error_work, 1);
  __PYX_XDEC_MEMVIEW(&p->tmp0, 1);
  __PYX_XDEC_MEMVIEW(&p->tmp1, 1);
  __PYX_XDEC_MEMVIEW(&p->tmp3, 1);
  __PYX_XDEC_MEMVIEW(&p->tmp2, 1);
  (*Py_TYPE(o)->tp_free)(o);
}

static int __pyx_tp_traverse_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter(PyObject *o, visitproc v, void *a) {
  int e;
  struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *p = (struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *)o;
  if (p->model) {
    e = (*v)(((PyObject*)p->model), a); if (e) return e;
  }
  return 0;
}

static int __pyx_tp_clear_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter(PyObject *o) {
  PyObject* tmp;
  struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *p = (struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter *)o;
  tmp = ((PyObject*)p->model);
  p->model = ((struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zStatespace *)Py_None); Py_INCREF(Py_None);
  Py_XDECREF(tmp);
  return 0;
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_model(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_5model_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_t(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_1t_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_tolerance(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_9tolerance_1__get__(o);
}

static int __pyx_setprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_tolerance(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
  if (v) {
    return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_9tolerance_3__set__(o, v);
  }
  else {
    PyErr_SetString(PyExc_NotImplementedError, "__del__");
    return -1;
  }
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_converged(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_9converged_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_period_converged(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_16period_converged_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_time_invariant(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_14time_invariant_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_filter_method(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_13filter_method_1__get__(o);
}

static int __pyx_setprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_filter_method(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
  if (v) {
    return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_13filter_method_3__set__(o, v);
  }
  else {
    PyErr_SetString(PyExc_NotImplementedError, "__del__");
    return -1;
  }
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_inversion_method(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_16inversion_method_1__get__(o);
}

static int __pyx_setprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_inversion_method(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
  if (v) {
    return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_16inversion_method_3__set__(o, v);
  }
  else {
    PyErr_SetString(PyExc_NotImplementedError, "__del__");
    return -1;
  }
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_stability_method(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_16stability_method_1__get__(o);
}

static int __pyx_setprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_stability_method(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
  if (v) {
    return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_16stability_method_3__set__(o, v);
  }
  else {
    PyErr_SetString(PyExc_NotImplementedError, "__del__");
    return -1;
  }
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_conserve_memory(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_15conserve_memory_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_loglikelihood_burn(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_18loglikelihood_burn_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_loglikelihood(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_13loglikelihood_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_filtered_state(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_14filtered_state_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_predicted_state(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_15predicted_state_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_forecast(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_8forecast_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_forecast_error(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_14forecast_error_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_filtered_state_cov(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_18filtered_state_cov_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_predicted_state_cov(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_19predicted_state_cov_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_forecast_error_cov(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_18forecast_error_cov_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_converged_forecast_error_cov(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_28converged_forecast_error_cov_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_converged_filtered_state_cov(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_28converged_filtered_state_cov_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_converged_predicted_state_cov(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_29converged_predicted_state_cov_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_converged_determinant(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_21converged_determinant_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_selected_obs(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_12selected_obs_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_selected_design(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_15selected_design_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_selected_obs_cov(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_16selected_obs_cov_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_forecast_error_fac(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_18forecast_error_fac_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_forecast_error_ipiv(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_19forecast_error_ipiv_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_forecast_error_work(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_19forecast_error_work_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_tmp0(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_4tmp0_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_tmp1(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_4tmp1_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_tmp3(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_4tmp3_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_tmp2(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_4tmp2_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_determinant(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_11determinant_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_k_endog(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_7k_endog_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_k_states(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_8k_states_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_k_posdef(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_8k_posdef_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_k_endog2(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_8k_endog2_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_k_states2(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_9k_states2_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_k_endogstates(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_13k_endogstates_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_ldwork(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_6ldwork_1__get__(o);
}

static PyMethodDef __pyx_methods_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter[] = {
  {"set_filter_method", (PyCFunction)__pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_3set_filter_method, METH_VARARGS|METH_KEYWORDS, __pyx_doc_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_2set_filter_method},
  {"seek", (PyCFunction)__pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_5seek, METH_VARARGS|METH_KEYWORDS, __pyx_doc_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_4seek},
  {"__next__", (PyCFunction)__pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_11__next__, METH_NOARGS|METH_COEXIST, __pyx_doc_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_10__next__},
  {"initialize_statespace_object_pointers", (PyCFunction)__pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_13initialize_statespace_object_pointers, METH_NOARGS, 0},
  {"initialize_filter_object_pointers", (PyCFunction)__pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_15initialize_filter_object_pointers, METH_NOARGS, 0},
  {"select_missing", (PyCFunction)__pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_17select_missing, METH_NOARGS, 0},
  {0, 0, 0, 0}
};

static struct PyGetSetDef __pyx_getsets_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter[] = {
  {(char *)"model", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_model, 0, 0, 0},
  {(char *)"t", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_t, 0, 0, 0},
  {(char *)"tolerance", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_tolerance, __pyx_setprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_tolerance, 0, 0},
  {(char *)"converged", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_converged, 0, 0, 0},
  {(char *)"period_converged", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_period_converged, 0, 0, 0},
  {(char *)"time_invariant", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_time_invariant, 0, 0, 0},
  {(char *)"filter_method", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_filter_method, __pyx_setprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_filter_method, 0, 0},
  {(char *)"inversion_method", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_inversion_method, __pyx_setprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_inversion_method, 0, 0},
  {(char *)"stability_method", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_stability_method, __pyx_setprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_stability_method, 0, 0},
  {(char *)"conserve_memory", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_conserve_memory, 0, 0, 0},
  {(char *)"loglikelihood_burn", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_loglikelihood_burn, 0, 0, 0},
  {(char *)"loglikelihood", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_loglikelihood, 0, 0, 0},
  {(char *)"filtered_state", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_filtered_state, 0, 0, 0},
  {(char *)"predicted_state", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_predicted_state, 0, 0, 0},
  {(char *)"forecast", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_forecast, 0, 0, 0},
  {(char *)"forecast_error", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_forecast_error, 0, 0, 0},
  {(char *)"filtered_state_cov", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_filtered_state_cov, 0, 0, 0},
  {(char *)"predicted_state_cov", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_predicted_state_cov, 0, 0, 0},
  {(char *)"forecast_error_cov", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_forecast_error_cov, 0, 0, 0},
  {(char *)"converged_forecast_error_cov", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_converged_forecast_error_cov, 0, 0, 0},
  {(char *)"converged_filtered_state_cov", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_converged_filtered_state_cov, 0, 0, 0},
  {(char *)"converged_predicted_state_cov", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_converged_predicted_state_cov, 0, 0, 0},
  {(char *)"converged_determinant", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_converged_determinant, 0, 0, 0},
  {(char *)"selected_obs", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_selected_obs, 0, 0, 0},
  {(char *)"selected_design", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_selected_design, 0, 0, 0},
  {(char *)"selected_obs_cov", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_selected_obs_cov, 0, 0, 0},
  {(char *)"forecast_error_fac", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_forecast_error_fac, 0, 0, 0},
  {(char *)"forecast_error_ipiv", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_forecast_error_ipiv, 0, 0, 0},
  {(char *)"forecast_error_work", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_forecast_error_work, 0, 0, 0},
  {(char *)"tmp0", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_tmp0, 0, 0, 0},
  {(char *)"tmp1", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_tmp1, 0, 0, 0},
  {(char *)"tmp3", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_tmp3, 0, 0, 0},
  {(char *)"tmp2", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_tmp2, 0, 0, 0},
  {(char *)"determinant", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_determinant, 0, 0, 0},
  {(char *)"k_endog", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_k_endog, 0, 0, 0},
  {(char *)"k_states", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_k_states, 0, 0, 0},
  {(char *)"k_posdef", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_k_posdef, 0, 0, 0},
  {(char *)"k_endog2", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_k_endog2, 0, 0, 0},
  {(char *)"k_states2", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_k_states2, 0, 0, 0},
  {(char *)"k_endogstates", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_k_endogstates, 0, 0, 0},
  {(char *)"ldwork", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_ldwork, 0, 0, 0},
  {0, 0, 0, 0, 0}
};

static PyTypeObject __pyx_type_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter = {
  PyVarObject_HEAD_INIT(0, 0)
  "statsmodels.tsa.statespace._statespace.zKalmanFilter", /*tp_name*/
  sizeof(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter), /*tp_basicsize*/
  0, /*tp_itemsize*/
  __pyx_tp_dealloc_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter, /*tp_dealloc*/
  0, /*tp_print*/
  0, /*tp_getattr*/
  0, /*tp_setattr*/
  #if PY_MAJOR_VERSION < 3
  0, /*tp_compare*/
  #else
  0, /*reserved*/
  #endif
  0, /*tp_repr*/
  0, /*tp_as_number*/
  0, /*tp_as_sequence*/
  0, /*tp_as_mapping*/
  0, /*tp_hash*/
  __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_9__call__, /*tp_call*/
  0, /*tp_str*/
  0, /*tp_getattro*/
  0, /*tp_setattro*/
  0, /*tp_as_buffer*/
  Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
  "\n    zKalmanFilter(model, filter=FILTER_CONVENTIONAL, inversion_method=INVERT_UNIVARIATE | SOLVE_CHOLESKY, stability_method=STABILITY_FORCE_SYMMETRY, tolerance=1e-19)\n\n    A representation of the Kalman filter recursions.\n\n    While the filter is mathematically represented as a recursion, it is here\n    translated into Python as a stateful iterator.\n\n    Because there are actually several types of Kalman filter depending on the\n    state space model of interest, this class only handles the *iteration*\n    aspect of filtering, and delegates the actual operations to four general\n    workhorse routines, which can be implemented separately for each type of\n    Kalman filter.\n\n    In order to maintain a consistent interface, and because these four general\n    routines may be quite different across filter types, their argument is only\n    the stateful ?KalmanFilter object. Furthermore, in order to allow the\n    different types of filter to substitute alternate matrices, this class\n    defines a set of pointers to the various state space arrays and the\n    filtering output arrays.\n\n    For example, handling missing observations requires not only substituting\n    `obs`, `design`, and `obs_cov` matrices, but the new matrices actually have\n    different dimensions than the originals. This can be flexibly accomodated\n    simply by replacing e.g. the `obs` pointer to the substituted `obs` array\n    and replacing `k_endog` for that iteration. Then in the next iteration, when\n    the `obs` vector may be missing different elements (or none at all), it can\n    again be redefined.\n\n    Each iteration of the filter (see `__next__`) proceeds in a number of\n    steps.\n\n    `initialize_object_pointers` initializes pointers to current-iteration\n    objects (i.e. the state space arrays and filter output arrays).  \n\n    `initialize_function_pointers` initializes pointers to the appropriate\n    Kalman filtering routines (i.e. `forecast_conventional` or\n    `forecast_exact_initial`, etc.).  \n\n    `select_arrays` converts the base arrays into \"selected\" arrays using\n    selection matrices. In particular, it handles the state covariance matrix\n    and redefined matrices based on missing values.  \n\n    `post_convergence` handles copying arrays from time $t-1$ to time $t$ when\n    the Kalman filter has converged and they don't need to be re-calculated.  \n\n    `forecasting` calls the Kalman filter `forcasting_<filter type>` routine\n\n    `inversion` calls the appropriate function to invert the forecast error\n    covariance matrix.  \n\n    `updating` calls the Kalman filter `updating_<filter type>` routine\n\n    `loglikelihood` calls the Kalman filter `loglikelihood_<filter type>` routine\n\n    `prediction` calls the Kalman filter `prediction_<filter type>` routine\n\n    `numerical_stability` performs end-of-iteration tasks to improve the numerical\n    stability of the filter \n\n    `check_convergence` checks for convergence of the filter to steady-state.\n    ", /*tp_doc*/
  __pyx_tp_traverse_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter, /*tp_traverse*/
  __pyx_tp_clear_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter, /*tp_clear*/
  0, /*tp_richcompare*/
  0, /*tp_weaklistoffset*/
  __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_7__iter__, /*tp_iter*/
  __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_11__next__, /*tp_iternext*/
  __pyx_methods_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter, /*tp_methods*/
  0, /*tp_members*/
  __pyx_getsets_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter, /*tp_getset*/
  0, /*tp_base*/
  0, /*tp_dict*/
  0, /*tp_descr_get*/
  0, /*tp_descr_set*/
  0, /*tp_dictoffset*/
  __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13zKalmanFilter_1__init__, /*tp_init*/
  0, /*tp_alloc*/
  __pyx_tp_new_11statsmodels_3tsa_10statespace_11_statespace_zKalmanFilter, /*tp_new*/
  0, /*tp_free*/
  0, /*tp_is_gc*/
  0, /*tp_bases*/
  0, /*tp_mro*/
  0, /*tp_cache*/
  0, /*tp_subclasses*/
  0, /*tp_weaklist*/
  0, /*tp_del*/
  0, /*tp_version_tag*/
  #if PY_VERSION_HEX >= 0x030400a1
  0, /*tp_finalize*/
  #endif
};

static PyObject *__pyx_tp_new_11statsmodels_3tsa_10statespace_11_statespace_dStatespace(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
  struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dStatespace *p;
  PyObject *o;
  if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
    o = (*t->tp_alloc)(t, 0);
  } else {
    o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
  }
  if (unlikely(!o)) return 0;
  p = ((struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dStatespace *)o);
  p->obs.data = NULL;
  p->obs.memview = NULL;
  p->obs_intercept.data = NULL;
  p->obs_intercept.memview = NULL;
  p->state_intercept.data = NULL;
  p->state_intercept.memview = NULL;
  p->initial_state.data = NULL;
  p->initial_state.memview = NULL;
  p->initial_state_cov.data = NULL;
  p->initial_state_cov.memview = NULL;
  p->design.data = NULL;
  p->design.memview = NULL;
  p->obs_cov.data = NULL;
  p->obs_cov.memview = NULL;
  p->transition.data = NULL;
  p->transition.memview = NULL;
  p->selection.data = NULL;
  p->selection.memview = NULL;
  p->state_cov.data = NULL;
  p->state_cov.memview = NULL;
  p->selected_state_cov.data = NULL;
  p->selected_state_cov.memview = NULL;
  p->missing.data = NULL;
  p->missing.memview = NULL;
  p->nmissing.data = NULL;
  p->nmissing.memview = NULL;
  p->tmp.data = NULL;
  p->tmp.memview = NULL;
  return o;
}

static void __pyx_tp_dealloc_11statsmodels_3tsa_10statespace_11_statespace_dStatespace(PyObject *o) {
  struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dStatespace *p = (struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dStatespace *)o;
  #if PY_VERSION_HEX >= 0x030400a1
  if (unlikely(Py_TYPE(o)->tp_finalize) && (!PyType_IS_GC(Py_TYPE(o)) || !_PyGC_FINALIZED(o))) {
    if (PyObject_CallFinalizerFromDealloc(o)) return;
  }
  #endif
  __PYX_XDEC_MEMVIEW(&p->obs, 1);
  __PYX_XDEC_MEMVIEW(&p->obs_intercept, 1);
  __PYX_XDEC_MEMVIEW(&p->state_intercept, 1);
  __PYX_XDEC_MEMVIEW(&p->initial_state, 1);
  __PYX_XDEC_MEMVIEW(&p->initial_state_cov, 1);
  __PYX_XDEC_MEMVIEW(&p->design, 1);
  __PYX_XDEC_MEMVIEW(&p->obs_cov, 1);
  __PYX_XDEC_MEMVIEW(&p->transition, 1);
  __PYX_XDEC_MEMVIEW(&p->selection, 1);
  __PYX_XDEC_MEMVIEW(&p->state_cov, 1);
  __PYX_XDEC_MEMVIEW(&p->selected_state_cov, 1);
  __PYX_XDEC_MEMVIEW(&p->missing, 1);
  __PYX_XDEC_MEMVIEW(&p->nmissing, 1);
  __PYX_XDEC_MEMVIEW(&p->tmp, 1);
  (*Py_TYPE(o)->tp_free)(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_nobs(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_4nobs_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_k_endog(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_7k_endog_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_k_states(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_8k_states_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_k_posdef(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_8k_posdef_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_obs(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_3obs_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_obs_intercept(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_13obs_intercept_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_state_intercept(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_15state_intercept_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_initial_state(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_13initial_state_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_initial_state_cov(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_17initial_state_cov_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_design(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_6design_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_obs_cov(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_7obs_cov_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_transition(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_10transition_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_selection(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_9selection_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_state_cov(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_9state_cov_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_selected_state_cov(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_18selected_state_cov_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_missing(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_7missing_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_nmissing(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_8nmissing_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_time_invariant(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_14time_invariant_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_initialized(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_11initialized_1__get__(o);
}

static PyMethodDef __pyx_methods_11statsmodels_3tsa_10statespace_11_statespace_dStatespace[] = {
  {"initialize_known", (PyCFunction)__pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_3initialize_known, METH_VARARGS|METH_KEYWORDS, __pyx_doc_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_2initialize_known},
  {"initialize_approximate_diffuse", (PyCFunction)__pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_5initialize_approximate_diffuse, METH_VARARGS|METH_KEYWORDS, __pyx_doc_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_4initialize_approximate_diffuse},
  {"initialize_stationary", (PyCFunction)__pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_7initialize_stationary, METH_VARARGS|METH_KEYWORDS, __pyx_doc_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_6initialize_stationary},
  {0, 0, 0, 0}
};

static struct PyGetSetDef __pyx_getsets_11statsmodels_3tsa_10statespace_11_statespace_dStatespace[] = {
  {(char *)"nobs", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_nobs, 0, 0, 0},
  {(char *)"k_endog", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_k_endog, 0, 0, 0},
  {(char *)"k_states", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_k_states, 0, 0, 0},
  {(char *)"k_posdef", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_k_posdef, 0, 0, 0},
  {(char *)"obs", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_obs, 0, 0, 0},
  {(char *)"obs_intercept", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_obs_intercept, 0, 0, 0},
  {(char *)"state_intercept", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_state_intercept, 0, 0, 0},
  {(char *)"initial_state", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_initial_state, 0, 0, 0},
  {(char *)"initial_state_cov", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_initial_state_cov, 0, 0, 0},
  {(char *)"design", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_design, 0, 0, 0},
  {(char *)"obs_cov", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_obs_cov, 0, 0, 0},
  {(char *)"transition", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_transition, 0, 0, 0},
  {(char *)"selection", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_selection, 0, 0, 0},
  {(char *)"state_cov", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_state_cov, 0, 0, 0},
  {(char *)"selected_state_cov", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_selected_state_cov, 0, 0, 0},
  {(char *)"missing", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_missing, 0, 0, 0},
  {(char *)"nmissing", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_nmissing, 0, 0, 0},
  {(char *)"time_invariant", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_time_invariant, 0, 0, 0},
  {(char *)"initialized", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_initialized, 0, 0, 0},
  {0, 0, 0, 0, 0}
};

static PyTypeObject __pyx_type_11statsmodels_3tsa_10statespace_11_statespace_dStatespace = {
  PyVarObject_HEAD_INIT(0, 0)
  "statsmodels.tsa.statespace._statespace.dStatespace", /*tp_name*/
  sizeof(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dStatespace), /*tp_basicsize*/
  0, /*tp_itemsize*/
  __pyx_tp_dealloc_11statsmodels_3tsa_10statespace_11_statespace_dStatespace, /*tp_dealloc*/
  0, /*tp_print*/
  0, /*tp_getattr*/
  0, /*tp_setattr*/
  #if PY_MAJOR_VERSION < 3
  0, /*tp_compare*/
  #else
  0, /*reserved*/
  #endif
  0, /*tp_repr*/
  0, /*tp_as_number*/
  0, /*tp_as_sequence*/
  0, /*tp_as_mapping*/
  0, /*tp_hash*/
  0, /*tp_call*/
  0, /*tp_str*/
  0, /*tp_getattro*/
  0, /*tp_setattro*/
  0, /*tp_as_buffer*/
  Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/
  "\n    dStatespace(obs, design, obs_intercept, obs_cov, transition, state_intercept, selection, state_cov)\n\n    *See Durbin and Koopman (2012), Chapter 4 for all notation*\n    ", /*tp_doc*/
  0, /*tp_traverse*/
  0, /*tp_clear*/
  0, /*tp_richcompare*/
  0, /*tp_weaklistoffset*/
  0, /*tp_iter*/
  0, /*tp_iternext*/
  __pyx_methods_11statsmodels_3tsa_10statespace_11_statespace_dStatespace, /*tp_methods*/
  0, /*tp_members*/
  __pyx_getsets_11statsmodels_3tsa_10statespace_11_statespace_dStatespace, /*tp_getset*/
  0, /*tp_base*/
  0, /*tp_dict*/
  0, /*tp_descr_get*/
  0, /*tp_descr_set*/
  0, /*tp_dictoffset*/
  __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11dStatespace_1__init__, /*tp_init*/
  0, /*tp_alloc*/
  __pyx_tp_new_11statsmodels_3tsa_10statespace_11_statespace_dStatespace, /*tp_new*/
  0, /*tp_free*/
  0, /*tp_is_gc*/
  0, /*tp_bases*/
  0, /*tp_mro*/
  0, /*tp_cache*/
  0, /*tp_subclasses*/
  0, /*tp_weaklist*/
  0, /*tp_del*/
  0, /*tp_version_tag*/
  #if PY_VERSION_HEX >= 0x030400a1
  0, /*tp_finalize*/
  #endif
};
static struct __pyx_vtabstruct_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter __pyx_vtable_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter;

static PyObject *__pyx_tp_new_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
  struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *p;
  PyObject *o;
  if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
    o = (*t->tp_alloc)(t, 0);
  } else {
    o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
  }
  if (unlikely(!o)) return 0;
  p = ((struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *)o);
  p->__pyx_vtab = __pyx_vtabptr_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter;
  p->model = ((struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dStatespace *)Py_None); Py_INCREF(Py_None);
  p->loglikelihood.data = NULL;
  p->loglikelihood.memview = NULL;
  p->filtered_state.data = NULL;
  p->filtered_state.memview = NULL;
  p->predicted_state.data = NULL;
  p->predicted_state.memview = NULL;
  p->forecast.data = NULL;
  p->forecast.memview = NULL;
  p->forecast_error.data = NULL;
  p->forecast_error.memview = NULL;
  p->filtered_state_cov.data = NULL;
  p->filtered_state_cov.memview = NULL;
  p->predicted_state_cov.data = NULL;
  p->predicted_state_cov.memview = NULL;
  p->forecast_error_cov.data = NULL;
  p->forecast_error_cov.memview = NULL;
  p->converged_forecast_error_cov.data = NULL;
  p->converged_forecast_error_cov.memview = NULL;
  p->converged_filtered_state_cov.data = NULL;
  p->converged_filtered_state_cov.memview = NULL;
  p->converged_predicted_state_cov.data = NULL;
  p->converged_predicted_state_cov.memview = NULL;
  p->selected_obs.data = NULL;
  p->selected_obs.memview = NULL;
  p->selected_design.data = NULL;
  p->selected_design.memview = NULL;
  p->selected_obs_cov.data = NULL;
  p->selected_obs_cov.memview = NULL;
  p->forecast_error_fac.data = NULL;
  p->forecast_error_fac.memview = NULL;
  p->forecast_error_ipiv.data = NULL;
  p->forecast_error_ipiv.memview = NULL;
  p->forecast_error_work.data = NULL;
  p->forecast_error_work.memview = NULL;
  p->tmp0.data = NULL;
  p->tmp0.memview = NULL;
  p->tmp1.data = NULL;
  p->tmp1.memview = NULL;
  p->tmp3.data = NULL;
  p->tmp3.memview = NULL;
  p->tmp2.data = NULL;
  p->tmp2.memview = NULL;
  return o;
}

static void __pyx_tp_dealloc_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter(PyObject *o) {
  struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *p = (struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *)o;
  #if PY_VERSION_HEX >= 0x030400a1
  if (unlikely(Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
    if (PyObject_CallFinalizerFromDealloc(o)) return;
  }
  #endif
  PyObject_GC_UnTrack(o);
  Py_CLEAR(p->model);
  __PYX_XDEC_MEMVIEW(&p->loglikelihood, 1);
  __PYX_XDEC_MEMVIEW(&p->filtered_state, 1);
  __PYX_XDEC_MEMVIEW(&p->predicted_state, 1);
  __PYX_XDEC_MEMVIEW(&p->forecast, 1);
  __PYX_XDEC_MEMVIEW(&p->forecast_error, 1);
  __PYX_XDEC_MEMVIEW(&p->filtered_state_cov, 1);
  __PYX_XDEC_MEMVIEW(&p->predicted_state_cov, 1);
  __PYX_XDEC_MEMVIEW(&p->forecast_error_cov, 1);
  __PYX_XDEC_MEMVIEW(&p->converged_forecast_error_cov, 1);
  __PYX_XDEC_MEMVIEW(&p->converged_filtered_state_cov, 1);
  __PYX_XDEC_MEMVIEW(&p->converged_predicted_state_cov, 1);
  __PYX_XDEC_MEMVIEW(&p->selected_obs, 1);
  __PYX_XDEC_MEMVIEW(&p->selected_design, 1);
  __PYX_XDEC_MEMVIEW(&p->selected_obs_cov, 1);
  __PYX_XDEC_MEMVIEW(&p->forecast_error_fac, 1);
  __PYX_XDEC_MEMVIEW(&p->forecast_error_ipiv, 1);
  __PYX_XDEC_MEMVIEW(&p->forecast_error_work, 1);
  __PYX_XDEC_MEMVIEW(&p->tmp0, 1);
  __PYX_XDEC_MEMVIEW(&p->tmp1, 1);
  __PYX_XDEC_MEMVIEW(&p->tmp3, 1);
  __PYX_XDEC_MEMVIEW(&p->tmp2, 1);
  (*Py_TYPE(o)->tp_free)(o);
}

static int __pyx_tp_traverse_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter(PyObject *o, visitproc v, void *a) {
  int e;
  struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *p = (struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *)o;
  if (p->model) {
    e = (*v)(((PyObject*)p->model), a); if (e) return e;
  }
  return 0;
}

static int __pyx_tp_clear_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter(PyObject *o) {
  PyObject* tmp;
  struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *p = (struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *)o;
  tmp = ((PyObject*)p->model);
  p->model = ((struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dStatespace *)Py_None); Py_INCREF(Py_None);
  Py_XDECREF(tmp);
  return 0;
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_model(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_5model_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_t(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_1t_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_tolerance(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_9tolerance_1__get__(o);
}

static int __pyx_setprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_tolerance(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
  if (v) {
    return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_9tolerance_3__set__(o, v);
  }
  else {
    PyErr_SetString(PyExc_NotImplementedError, "__del__");
    return -1;
  }
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_converged(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_9converged_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_period_converged(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_16period_converged_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_time_invariant(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_14time_invariant_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_filter_method(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_13filter_method_1__get__(o);
}

static int __pyx_setprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_filter_method(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
  if (v) {
    return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_13filter_method_3__set__(o, v);
  }
  else {
    PyErr_SetString(PyExc_NotImplementedError, "__del__");
    return -1;
  }
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_inversion_method(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_16inversion_method_1__get__(o);
}

static int __pyx_setprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_inversion_method(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
  if (v) {
    return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_16inversion_method_3__set__(o, v);
  }
  else {
    PyErr_SetString(PyExc_NotImplementedError, "__del__");
    return -1;
  }
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_stability_method(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_16stability_method_1__get__(o);
}

static int __pyx_setprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_stability_method(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
  if (v) {
    return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_16stability_method_3__set__(o, v);
  }
  else {
    PyErr_SetString(PyExc_NotImplementedError, "__del__");
    return -1;
  }
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_conserve_memory(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_15conserve_memory_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_loglikelihood_burn(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_18loglikelihood_burn_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_loglikelihood(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_13loglikelihood_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_filtered_state(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_14filtered_state_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_predicted_state(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_15predicted_state_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_forecast(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_8forecast_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_forecast_error(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_14forecast_error_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_filtered_state_cov(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_18filtered_state_cov_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_predicted_state_cov(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_19predicted_state_cov_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_forecast_error_cov(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_18forecast_error_cov_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_converged_forecast_error_cov(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_28converged_forecast_error_cov_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_converged_filtered_state_cov(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_28converged_filtered_state_cov_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_converged_predicted_state_cov(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_29converged_predicted_state_cov_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_converged_determinant(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_21converged_determinant_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_selected_obs(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_12selected_obs_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_selected_design(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_15selected_design_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_selected_obs_cov(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_16selected_obs_cov_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_forecast_error_fac(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_18forecast_error_fac_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_forecast_error_ipiv(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_19forecast_error_ipiv_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_forecast_error_work(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_19forecast_error_work_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_tmp0(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_4tmp0_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_tmp1(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_4tmp1_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_tmp3(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_4tmp3_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_tmp2(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_4tmp2_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_determinant(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_11determinant_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_k_endog(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_7k_endog_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_k_states(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_8k_states_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_k_posdef(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_8k_posdef_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_k_endog2(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_8k_endog2_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_k_states2(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_9k_states2_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_k_endogstates(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_13k_endogstates_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_ldwork(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_6ldwork_1__get__(o);
}

static PyMethodDef __pyx_methods_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter[] = {
  {"set_filter_method", (PyCFunction)__pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_3set_filter_method, METH_VARARGS|METH_KEYWORDS, __pyx_doc_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_2set_filter_method},
  {"seek", (PyCFunction)__pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_5seek, METH_VARARGS|METH_KEYWORDS, __pyx_doc_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_4seek},
  {"__next__", (PyCFunction)__pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_11__next__, METH_NOARGS|METH_COEXIST, __pyx_doc_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_10__next__},
  {"initialize_statespace_object_pointers", (PyCFunction)__pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_13initialize_statespace_object_pointers, METH_NOARGS, 0},
  {"initialize_filter_object_pointers", (PyCFunction)__pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_15initialize_filter_object_pointers, METH_NOARGS, 0},
  {"select_missing", (PyCFunction)__pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_17select_missing, METH_NOARGS, 0},
  {0, 0, 0, 0}
};

static struct PyGetSetDef __pyx_getsets_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter[] = {
  {(char *)"model", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_model, 0, 0, 0},
  {(char *)"t", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_t, 0, 0, 0},
  {(char *)"tolerance", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_tolerance, __pyx_setprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_tolerance, 0, 0},
  {(char *)"converged", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_converged, 0, 0, 0},
  {(char *)"period_converged", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_period_converged, 0, 0, 0},
  {(char *)"time_invariant", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_time_invariant, 0, 0, 0},
  {(char *)"filter_method", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_filter_method, __pyx_setprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_filter_method, 0, 0},
  {(char *)"inversion_method", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_inversion_method, __pyx_setprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_inversion_method, 0, 0},
  {(char *)"stability_method", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_stability_method, __pyx_setprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_stability_method, 0, 0},
  {(char *)"conserve_memory", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_conserve_memory, 0, 0, 0},
  {(char *)"loglikelihood_burn", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_loglikelihood_burn, 0, 0, 0},
  {(char *)"loglikelihood", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_loglikelihood, 0, 0, 0},
  {(char *)"filtered_state", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_filtered_state, 0, 0, 0},
  {(char *)"predicted_state", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_predicted_state, 0, 0, 0},
  {(char *)"forecast", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_forecast, 0, 0, 0},
  {(char *)"forecast_error", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_forecast_error, 0, 0, 0},
  {(char *)"filtered_state_cov", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_filtered_state_cov, 0, 0, 0},
  {(char *)"predicted_state_cov", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_predicted_state_cov, 0, 0, 0},
  {(char *)"forecast_error_cov", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_forecast_error_cov, 0, 0, 0},
  {(char *)"converged_forecast_error_cov", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_converged_forecast_error_cov, 0, 0, 0},
  {(char *)"converged_filtered_state_cov", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_converged_filtered_state_cov, 0, 0, 0},
  {(char *)"converged_predicted_state_cov", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_converged_predicted_state_cov, 0, 0, 0},
  {(char *)"converged_determinant", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_converged_determinant, 0, 0, 0},
  {(char *)"selected_obs", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_selected_obs, 0, 0, 0},
  {(char *)"selected_design", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_selected_design, 0, 0, 0},
  {(char *)"selected_obs_cov", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_selected_obs_cov, 0, 0, 0},
  {(char *)"forecast_error_fac", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_forecast_error_fac, 0, 0, 0},
  {(char *)"forecast_error_ipiv", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_forecast_error_ipiv, 0, 0, 0},
  {(char *)"forecast_error_work", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_forecast_error_work, 0, 0, 0},
  {(char *)"tmp0", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_tmp0, 0, 0, 0},
  {(char *)"tmp1", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_tmp1, 0, 0, 0},
  {(char *)"tmp3", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_tmp3, 0, 0, 0},
  {(char *)"tmp2", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_tmp2, 0, 0, 0},
  {(char *)"determinant", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_determinant, 0, 0, 0},
  {(char *)"k_endog", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_k_endog, 0, 0, 0},
  {(char *)"k_states", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_k_states, 0, 0, 0},
  {(char *)"k_posdef", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_k_posdef, 0, 0, 0},
  {(char *)"k_endog2", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_k_endog2, 0, 0, 0},
  {(char *)"k_states2", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_k_states2, 0, 0, 0},
  {(char *)"k_endogstates", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_k_endogstates, 0, 0, 0},
  {(char *)"ldwork", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_ldwork, 0, 0, 0},
  {0, 0, 0, 0, 0}
};

static PyTypeObject __pyx_type_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter = {
  PyVarObject_HEAD_INIT(0, 0)
  "statsmodels.tsa.statespace._statespace.dKalmanFilter", /*tp_name*/
  sizeof(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter), /*tp_basicsize*/
  0, /*tp_itemsize*/
  __pyx_tp_dealloc_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter, /*tp_dealloc*/
  0, /*tp_print*/
  0, /*tp_getattr*/
  0, /*tp_setattr*/
  #if PY_MAJOR_VERSION < 3
  0, /*tp_compare*/
  #else
  0, /*reserved*/
  #endif
  0, /*tp_repr*/
  0, /*tp_as_number*/
  0, /*tp_as_sequence*/
  0, /*tp_as_mapping*/
  0, /*tp_hash*/
  __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_9__call__, /*tp_call*/
  0, /*tp_str*/
  0, /*tp_getattro*/
  0, /*tp_setattro*/
  0, /*tp_as_buffer*/
  Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
  "\n    dKalmanFilter(model, filter=FILTER_CONVENTIONAL, inversion_method=INVERT_UNIVARIATE | SOLVE_CHOLESKY, stability_method=STABILITY_FORCE_SYMMETRY, tolerance=1e-19)\n\n    A representation of the Kalman filter recursions.\n\n    While the filter is mathematically represented as a recursion, it is here\n    translated into Python as a stateful iterator.\n\n    Because there are actually several types of Kalman filter depending on the\n    state space model of interest, this class only handles the *iteration*\n    aspect of filtering, and delegates the actual operations to four general\n    workhorse routines, which can be implemented separately for each type of\n    Kalman filter.\n\n    In order to maintain a consistent interface, and because these four general\n    routines may be quite different across filter types, their argument is only\n    the stateful ?KalmanFilter object. Furthermore, in order to allow the\n    different types of filter to substitute alternate matrices, this class\n    defines a set of pointers to the various state space arrays and the\n    filtering output arrays.\n\n    For example, handling missing observations requires not only substituting\n    `obs`, `design`, and `obs_cov` matrices, but the new matrices actually have\n    different dimensions than the originals. This can be flexibly accomodated\n    simply by replacing e.g. the `obs` pointer to the substituted `obs` array\n    and replacing `k_endog` for that iteration. Then in the next iteration, when\n    the `obs` vector may be missing different elements (or none at all), it can\n    again be redefined.\n\n    Each iteration of the filter (see `__next__`) proceeds in a number of\n    steps.\n\n    `initialize_object_pointers` initializes pointers to current-iteration\n    objects (i.e. the state space arrays and filter output arrays).  \n\n    `initialize_function_pointers` initializes pointers to the appropriate\n    Kalman filtering routines (i.e. `forecast_conventional` or\n    `forecast_exact_initial`, etc.).  \n\n    `select_arrays` converts the base arrays into \"selected\" arrays using\n    selection matrices. In particular, it handles the state covariance matrix\n    and redefined matrices based on missing values.  \n\n    `post_convergence` handles copying arrays from time $t-1$ to time $t$ when\n    the Kalman filter has converged and they don't need to be re-calculated.  \n\n    `forecasting` calls the Kalman filter `forcasting_<filter type>` routine\n\n    `inversion` calls the appropriate function to invert the forecast error\n    covariance matrix.  \n\n    `updating` calls the Kalman filter `updating_<filter type>` routine\n\n    `loglikelihood` calls the Kalman filter `loglikelihood_<filter type>` routine\n\n    `prediction` calls the Kalman filter `prediction_<filter type>` routine\n\n    `numerical_stability` performs end-of-iteration tasks to improve the numerical\n    stability of the filter \n\n    `check_convergence` checks for convergence of the filter to steady-state.\n    ", /*tp_doc*/
  __pyx_tp_traverse_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter, /*tp_traverse*/
  __pyx_tp_clear_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter, /*tp_clear*/
  0, /*tp_richcompare*/
  0, /*tp_weaklistoffset*/
  __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_7__iter__, /*tp_iter*/
  __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_11__next__, /*tp_iternext*/
  __pyx_methods_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter, /*tp_methods*/
  0, /*tp_members*/
  __pyx_getsets_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter, /*tp_getset*/
  0, /*tp_base*/
  0, /*tp_dict*/
  0, /*tp_descr_get*/
  0, /*tp_descr_set*/
  0, /*tp_dictoffset*/
  __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_1__init__, /*tp_init*/
  0, /*tp_alloc*/
  __pyx_tp_new_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter, /*tp_new*/
  0, /*tp_free*/
  0, /*tp_is_gc*/
  0, /*tp_bases*/
  0, /*tp_mro*/
  0, /*tp_cache*/
  0, /*tp_subclasses*/
  0, /*tp_weaklist*/
  0, /*tp_del*/
  0, /*tp_version_tag*/
  #if PY_VERSION_HEX >= 0x030400a1
  0, /*tp_finalize*/
  #endif
};

static PyObject *__pyx_tp_new_11statsmodels_3tsa_10statespace_11_statespace_cStatespace(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
  struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cStatespace *p;
  PyObject *o;
  if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
    o = (*t->tp_alloc)(t, 0);
  } else {
    o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
  }
  if (unlikely(!o)) return 0;
  p = ((struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cStatespace *)o);
  p->obs.data = NULL;
  p->obs.memview = NULL;
  p->obs_intercept.data = NULL;
  p->obs_intercept.memview = NULL;
  p->state_intercept.data = NULL;
  p->state_intercept.memview = NULL;
  p->initial_state.data = NULL;
  p->initial_state.memview = NULL;
  p->initial_state_cov.data = NULL;
  p->initial_state_cov.memview = NULL;
  p->design.data = NULL;
  p->design.memview = NULL;
  p->obs_cov.data = NULL;
  p->obs_cov.memview = NULL;
  p->transition.data = NULL;
  p->transition.memview = NULL;
  p->selection.data = NULL;
  p->selection.memview = NULL;
  p->state_cov.data = NULL;
  p->state_cov.memview = NULL;
  p->selected_state_cov.data = NULL;
  p->selected_state_cov.memview = NULL;
  p->missing.data = NULL;
  p->missing.memview = NULL;
  p->nmissing.data = NULL;
  p->nmissing.memview = NULL;
  p->tmp.data = NULL;
  p->tmp.memview = NULL;
  return o;
}

static void __pyx_tp_dealloc_11statsmodels_3tsa_10statespace_11_statespace_cStatespace(PyObject *o) {
  struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cStatespace *p = (struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cStatespace *)o;
  #if PY_VERSION_HEX >= 0x030400a1
  if (unlikely(Py_TYPE(o)->tp_finalize) && (!PyType_IS_GC(Py_TYPE(o)) || !_PyGC_FINALIZED(o))) {
    if (PyObject_CallFinalizerFromDealloc(o)) return;
  }
  #endif
  __PYX_XDEC_MEMVIEW(&p->obs, 1);
  __PYX_XDEC_MEMVIEW(&p->obs_intercept, 1);
  __PYX_XDEC_MEMVIEW(&p->state_intercept, 1);
  __PYX_XDEC_MEMVIEW(&p->initial_state, 1);
  __PYX_XDEC_MEMVIEW(&p->initial_state_cov, 1);
  __PYX_XDEC_MEMVIEW(&p->design, 1);
  __PYX_XDEC_MEMVIEW(&p->obs_cov, 1);
  __PYX_XDEC_MEMVIEW(&p->transition, 1);
  __PYX_XDEC_MEMVIEW(&p->selection, 1);
  __PYX_XDEC_MEMVIEW(&p->state_cov, 1);
  __PYX_XDEC_MEMVIEW(&p->selected_state_cov, 1);
  __PYX_XDEC_MEMVIEW(&p->missing, 1);
  __PYX_XDEC_MEMVIEW(&p->nmissing, 1);
  __PYX_XDEC_MEMVIEW(&p->tmp, 1);
  (*Py_TYPE(o)->tp_free)(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_nobs(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_4nobs_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_k_endog(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_7k_endog_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_k_states(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_8k_states_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_k_posdef(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_8k_posdef_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_obs(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_3obs_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_obs_intercept(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_13obs_intercept_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_state_intercept(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_15state_intercept_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_initial_state(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_13initial_state_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_initial_state_cov(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_17initial_state_cov_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_design(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_6design_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_obs_cov(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_7obs_cov_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_transition(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_10transition_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_selection(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_9selection_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_state_cov(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_9state_cov_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_selected_state_cov(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_18selected_state_cov_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_missing(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_7missing_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_nmissing(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_8nmissing_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_time_invariant(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_14time_invariant_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_initialized(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_11initialized_1__get__(o);
}

static PyMethodDef __pyx_methods_11statsmodels_3tsa_10statespace_11_statespace_cStatespace[] = {
  {"initialize_known", (PyCFunction)__pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_3initialize_known, METH_VARARGS|METH_KEYWORDS, __pyx_doc_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_2initialize_known},
  {"initialize_approximate_diffuse", (PyCFunction)__pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_5initialize_approximate_diffuse, METH_VARARGS|METH_KEYWORDS, __pyx_doc_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_4initialize_approximate_diffuse},
  {"initialize_stationary", (PyCFunction)__pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_7initialize_stationary, METH_VARARGS|METH_KEYWORDS, __pyx_doc_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_6initialize_stationary},
  {0, 0, 0, 0}
};

static struct PyGetSetDef __pyx_getsets_11statsmodels_3tsa_10statespace_11_statespace_cStatespace[] = {
  {(char *)"nobs", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_nobs, 0, 0, 0},
  {(char *)"k_endog", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_k_endog, 0, 0, 0},
  {(char *)"k_states", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_k_states, 0, 0, 0},
  {(char *)"k_posdef", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_k_posdef, 0, 0, 0},
  {(char *)"obs", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_obs, 0, 0, 0},
  {(char *)"obs_intercept", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_obs_intercept, 0, 0, 0},
  {(char *)"state_intercept", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_state_intercept, 0, 0, 0},
  {(char *)"initial_state", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_initial_state, 0, 0, 0},
  {(char *)"initial_state_cov", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_initial_state_cov, 0, 0, 0},
  {(char *)"design", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_design, 0, 0, 0},
  {(char *)"obs_cov", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_obs_cov, 0, 0, 0},
  {(char *)"transition", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_transition, 0, 0, 0},
  {(char *)"selection", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_selection, 0, 0, 0},
  {(char *)"state_cov", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_state_cov, 0, 0, 0},
  {(char *)"selected_state_cov", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_selected_state_cov, 0, 0, 0},
  {(char *)"missing", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_missing, 0, 0, 0},
  {(char *)"nmissing", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_nmissing, 0, 0, 0},
  {(char *)"time_invariant", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_time_invariant, 0, 0, 0},
  {(char *)"initialized", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_initialized, 0, 0, 0},
  {0, 0, 0, 0, 0}
};

static PyTypeObject __pyx_type_11statsmodels_3tsa_10statespace_11_statespace_cStatespace = {
  PyVarObject_HEAD_INIT(0, 0)
  "statsmodels.tsa.statespace._statespace.cStatespace", /*tp_name*/
  sizeof(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cStatespace), /*tp_basicsize*/
  0, /*tp_itemsize*/
  __pyx_tp_dealloc_11statsmodels_3tsa_10statespace_11_statespace_cStatespace, /*tp_dealloc*/
  0, /*tp_print*/
  0, /*tp_getattr*/
  0, /*tp_setattr*/
  #if PY_MAJOR_VERSION < 3
  0, /*tp_compare*/
  #else
  0, /*reserved*/
  #endif
  0, /*tp_repr*/
  0, /*tp_as_number*/
  0, /*tp_as_sequence*/
  0, /*tp_as_mapping*/
  0, /*tp_hash*/
  0, /*tp_call*/
  0, /*tp_str*/
  0, /*tp_getattro*/
  0, /*tp_setattro*/
  0, /*tp_as_buffer*/
  Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/
  "\n    cStatespace(obs, design, obs_intercept, obs_cov, transition, state_intercept, selection, state_cov)\n\n    *See Durbin and Koopman (2012), Chapter 4 for all notation*\n    ", /*tp_doc*/
  0, /*tp_traverse*/
  0, /*tp_clear*/
  0, /*tp_richcompare*/
  0, /*tp_weaklistoffset*/
  0, /*tp_iter*/
  0, /*tp_iternext*/
  __pyx_methods_11statsmodels_3tsa_10statespace_11_statespace_cStatespace, /*tp_methods*/
  0, /*tp_members*/
  __pyx_getsets_11statsmodels_3tsa_10statespace_11_statespace_cStatespace, /*tp_getset*/
  0, /*tp_base*/
  0, /*tp_dict*/
  0, /*tp_descr_get*/
  0, /*tp_descr_set*/
  0, /*tp_dictoffset*/
  __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11cStatespace_1__init__, /*tp_init*/
  0, /*tp_alloc*/
  __pyx_tp_new_11statsmodels_3tsa_10statespace_11_statespace_cStatespace, /*tp_new*/
  0, /*tp_free*/
  0, /*tp_is_gc*/
  0, /*tp_bases*/
  0, /*tp_mro*/
  0, /*tp_cache*/
  0, /*tp_subclasses*/
  0, /*tp_weaklist*/
  0, /*tp_del*/
  0, /*tp_version_tag*/
  #if PY_VERSION_HEX >= 0x030400a1
  0, /*tp_finalize*/
  #endif
};
static struct __pyx_vtabstruct_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter __pyx_vtable_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter;

static PyObject *__pyx_tp_new_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
  struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *p;
  PyObject *o;
  if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
    o = (*t->tp_alloc)(t, 0);
  } else {
    o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
  }
  if (unlikely(!o)) return 0;
  p = ((struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *)o);
  p->__pyx_vtab = __pyx_vtabptr_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter;
  p->model = ((struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cStatespace *)Py_None); Py_INCREF(Py_None);
  p->loglikelihood.data = NULL;
  p->loglikelihood.memview = NULL;
  p->filtered_state.data = NULL;
  p->filtered_state.memview = NULL;
  p->predicted_state.data = NULL;
  p->predicted_state.memview = NULL;
  p->forecast.data = NULL;
  p->forecast.memview = NULL;
  p->forecast_error.data = NULL;
  p->forecast_error.memview = NULL;
  p->filtered_state_cov.data = NULL;
  p->filtered_state_cov.memview = NULL;
  p->predicted_state_cov.data = NULL;
  p->predicted_state_cov.memview = NULL;
  p->forecast_error_cov.data = NULL;
  p->forecast_error_cov.memview = NULL;
  p->converged_forecast_error_cov.data = NULL;
  p->converged_forecast_error_cov.memview = NULL;
  p->converged_filtered_state_cov.data = NULL;
  p->converged_filtered_state_cov.memview = NULL;
  p->converged_predicted_state_cov.data = NULL;
  p->converged_predicted_state_cov.memview = NULL;
  p->selected_obs.data = NULL;
  p->selected_obs.memview = NULL;
  p->selected_design.data = NULL;
  p->selected_design.memview = NULL;
  p->selected_obs_cov.data = NULL;
  p->selected_obs_cov.memview = NULL;
  p->forecast_error_fac.data = NULL;
  p->forecast_error_fac.memview = NULL;
  p->forecast_error_ipiv.data = NULL;
  p->forecast_error_ipiv.memview = NULL;
  p->forecast_error_work.data = NULL;
  p->forecast_error_work.memview = NULL;
  p->tmp0.data = NULL;
  p->tmp0.memview = NULL;
  p->tmp1.data = NULL;
  p->tmp1.memview = NULL;
  p->tmp3.data = NULL;
  p->tmp3.memview = NULL;
  p->tmp2.data = NULL;
  p->tmp2.memview = NULL;
  return o;
}

static void __pyx_tp_dealloc_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter(PyObject *o) {
  struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *p = (struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *)o;
  #if PY_VERSION_HEX >= 0x030400a1
  if (unlikely(Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
    if (PyObject_CallFinalizerFromDealloc(o)) return;
  }
  #endif
  PyObject_GC_UnTrack(o);
  Py_CLEAR(p->model);
  __PYX_XDEC_MEMVIEW(&p->loglikelihood, 1);
  __PYX_XDEC_MEMVIEW(&p->filtered_state, 1);
  __PYX_XDEC_MEMVIEW(&p->predicted_state, 1);
  __PYX_XDEC_MEMVIEW(&p->forecast, 1);
  __PYX_XDEC_MEMVIEW(&p->forecast_error, 1);
  __PYX_XDEC_MEMVIEW(&p->filtered_state_cov, 1);
  __PYX_XDEC_MEMVIEW(&p->predicted_state_cov, 1);
  __PYX_XDEC_MEMVIEW(&p->forecast_error_cov, 1);
  __PYX_XDEC_MEMVIEW(&p->converged_forecast_error_cov, 1);
  __PYX_XDEC_MEMVIEW(&p->converged_filtered_state_cov, 1);
  __PYX_XDEC_MEMVIEW(&p->converged_predicted_state_cov, 1);
  __PYX_XDEC_MEMVIEW(&p->selected_obs, 1);
  __PYX_XDEC_MEMVIEW(&p->selected_design, 1);
  __PYX_XDEC_MEMVIEW(&p->selected_obs_cov, 1);
  __PYX_XDEC_MEMVIEW(&p->forecast_error_fac, 1);
  __PYX_XDEC_MEMVIEW(&p->forecast_error_ipiv, 1);
  __PYX_XDEC_MEMVIEW(&p->forecast_error_work, 1);
  __PYX_XDEC_MEMVIEW(&p->tmp0, 1);
  __PYX_XDEC_MEMVIEW(&p->tmp1, 1);
  __PYX_XDEC_MEMVIEW(&p->tmp3, 1);
  __PYX_XDEC_MEMVIEW(&p->tmp2, 1);
  (*Py_TYPE(o)->tp_free)(o);
}

static int __pyx_tp_traverse_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter(PyObject *o, visitproc v, void *a) {
  int e;
  struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *p = (struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *)o;
  if (p->model) {
    e = (*v)(((PyObject*)p->model), a); if (e) return e;
  }
  return 0;
}

static int __pyx_tp_clear_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter(PyObject *o) {
  PyObject* tmp;
  struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *p = (struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *)o;
  tmp = ((PyObject*)p->model);
  p->model = ((struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cStatespace *)Py_None); Py_INCREF(Py_None);
  Py_XDECREF(tmp);
  return 0;
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_model(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_5model_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_t(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_1t_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_tolerance(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_9tolerance_1__get__(o);
}

static int __pyx_setprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_tolerance(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
  if (v) {
    return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_9tolerance_3__set__(o, v);
  }
  else {
    PyErr_SetString(PyExc_NotImplementedError, "__del__");
    return -1;
  }
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_converged(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_9converged_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_period_converged(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_16period_converged_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_time_invariant(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_14time_invariant_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_filter_method(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_13filter_method_1__get__(o);
}

static int __pyx_setprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_filter_method(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
  if (v) {
    return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_13filter_method_3__set__(o, v);
  }
  else {
    PyErr_SetString(PyExc_NotImplementedError, "__del__");
    return -1;
  }
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_inversion_method(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_16inversion_method_1__get__(o);
}

static int __pyx_setprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_inversion_method(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
  if (v) {
    return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_16inversion_method_3__set__(o, v);
  }
  else {
    PyErr_SetString(PyExc_NotImplementedError, "__del__");
    return -1;
  }
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_stability_method(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_16stability_method_1__get__(o);
}

static int __pyx_setprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_stability_method(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
  if (v) {
    return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_16stability_method_3__set__(o, v);
  }
  else {
    PyErr_SetString(PyExc_NotImplementedError, "__del__");
    return -1;
  }
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_conserve_memory(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_15conserve_memory_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_loglikelihood_burn(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_18loglikelihood_burn_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_loglikelihood(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_13loglikelihood_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_filtered_state(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_14filtered_state_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_predicted_state(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_15predicted_state_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_forecast(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_8forecast_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_forecast_error(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_14forecast_error_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_filtered_state_cov(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_18filtered_state_cov_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_predicted_state_cov(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_19predicted_state_cov_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_forecast_error_cov(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_18forecast_error_cov_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_converged_forecast_error_cov(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_28converged_forecast_error_cov_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_converged_filtered_state_cov(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_28converged_filtered_state_cov_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_converged_predicted_state_cov(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_29converged_predicted_state_cov_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_converged_determinant(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_21converged_determinant_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_selected_obs(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_12selected_obs_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_selected_design(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_15selected_design_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_selected_obs_cov(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_16selected_obs_cov_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_forecast_error_fac(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_18forecast_error_fac_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_forecast_error_ipiv(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_19forecast_error_ipiv_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_forecast_error_work(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_19forecast_error_work_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_tmp0(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_4tmp0_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_tmp1(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_4tmp1_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_tmp3(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_4tmp3_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_tmp2(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_4tmp2_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_determinant(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_11determinant_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_k_endog(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_7k_endog_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_k_states(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_8k_states_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_k_posdef(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_8k_posdef_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_k_endog2(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_8k_endog2_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_k_states2(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_9k_states2_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_k_endogstates(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_13k_endogstates_1__get__(o);
}

static PyObject *__pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_ldwork(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_6ldwork_1__get__(o);
}

static PyMethodDef __pyx_methods_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter[] = {
  {"set_filter_method", (PyCFunction)__pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_3set_filter_method, METH_VARARGS|METH_KEYWORDS, __pyx_doc_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_2set_filter_method},
  {"seek", (PyCFunction)__pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_5seek, METH_VARARGS|METH_KEYWORDS, __pyx_doc_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_4seek},
  {"__next__", (PyCFunction)__pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_11__next__, METH_NOARGS|METH_COEXIST, __pyx_doc_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_10__next__},
  {"initialize_statespace_object_pointers", (PyCFunction)__pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_13initialize_statespace_object_pointers, METH_NOARGS, 0},
  {"initialize_filter_object_pointers", (PyCFunction)__pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_15initialize_filter_object_pointers, METH_NOARGS, 0},
  {"select_missing", (PyCFunction)__pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_17select_missing, METH_NOARGS, 0},
  {0, 0, 0, 0}
};

static struct PyGetSetDef __pyx_getsets_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter[] = {
  {(char *)"model", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_model, 0, 0, 0},
  {(char *)"t", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_t, 0, 0, 0},
  {(char *)"tolerance", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_tolerance, __pyx_setprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_tolerance, 0, 0},
  {(char *)"converged", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_converged, 0, 0, 0},
  {(char *)"period_converged", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_period_converged, 0, 0, 0},
  {(char *)"time_invariant", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_time_invariant, 0, 0, 0},
  {(char *)"filter_method", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_filter_method, __pyx_setprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_filter_method, 0, 0},
  {(char *)"inversion_method", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_inversion_method, __pyx_setprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_inversion_method, 0, 0},
  {(char *)"stability_method", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_stability_method, __pyx_setprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_stability_method, 0, 0},
  {(char *)"conserve_memory", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_conserve_memory, 0, 0, 0},
  {(char *)"loglikelihood_burn", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_loglikelihood_burn, 0, 0, 0},
  {(char *)"loglikelihood", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_loglikelihood, 0, 0, 0},
  {(char *)"filtered_state", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_filtered_state, 0, 0, 0},
  {(char *)"predicted_state", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_predicted_state, 0, 0, 0},
  {(char *)"forecast", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_forecast, 0, 0, 0},
  {(char *)"forecast_error", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_forecast_error, 0, 0, 0},
  {(char *)"filtered_state_cov", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_filtered_state_cov, 0, 0, 0},
  {(char *)"predicted_state_cov", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_predicted_state_cov, 0, 0, 0},
  {(char *)"forecast_error_cov", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_forecast_error_cov, 0, 0, 0},
  {(char *)"converged_forecast_error_cov", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_converged_forecast_error_cov, 0, 0, 0},
  {(char *)"converged_filtered_state_cov", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_converged_filtered_state_cov, 0, 0, 0},
  {(char *)"converged_predicted_state_cov", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_converged_predicted_state_cov, 0, 0, 0},
  {(char *)"converged_determinant", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_converged_determinant, 0, 0, 0},
  {(char *)"selected_obs", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_selected_obs, 0, 0, 0},
  {(char *)"selected_design", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_selected_design, 0, 0, 0},
  {(char *)"selected_obs_cov", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_selected_obs_cov, 0, 0, 0},
  {(char *)"forecast_error_fac", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_forecast_error_fac, 0, 0, 0},
  {(char *)"forecast_error_ipiv", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_forecast_error_ipiv, 0, 0, 0},
  {(char *)"forecast_error_work", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_forecast_error_work, 0, 0, 0},
  {(char *)"tmp0", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_tmp0, 0, 0, 0},
  {(char *)"tmp1", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_tmp1, 0, 0, 0},
  {(char *)"tmp3", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_tmp3, 0, 0, 0},
  {(char *)"tmp2", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_tmp2, 0, 0, 0},
  {(char *)"determinant", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_determinant, 0, 0, 0},
  {(char *)"k_endog", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_k_endog, 0, 0, 0},
  {(char *)"k_states", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_k_states, 0, 0, 0},
  {(char *)"k_posdef", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_k_posdef, 0, 0, 0},
  {(char *)"k_endog2", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_k_endog2, 0, 0, 0},
  {(char *)"k_states2", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_k_states2, 0, 0, 0},
  {(char *)"k_endogstates", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_k_endogstates, 0, 0, 0},
  {(char *)"ldwork", __pyx_getprop_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_ldwork, 0, 0, 0},
  {0, 0, 0, 0, 0}
};

static PyTypeObject __pyx_type_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter = {
  PyVarObject_HEAD_INIT(0, 0)
  "statsmodels.tsa.statespace._statespace.cKalmanFilter", /*tp_name*/
  sizeof(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter), /*tp_basicsize*/
  0, /*tp_itemsize*/
  __pyx_tp_dealloc_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter, /*tp_dealloc*/
  0, /*tp_print*/
  0, /*tp_getattr*/
  0, /*tp_setattr*/
  #if PY_MAJOR_VERSION < 3
  0, /*tp_compare*/
  #else
  0, /*reserved*/
  #endif
  0, /*tp_repr*/
  0, /*tp_as_number*/
  0, /*tp_as_sequence*/
  0, /*tp_as_mapping*/
  0, /*tp_hash*/
  __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_9__call__, /*tp_call*/
  0, /*tp_str*/
  0, /*tp_getattro*/
  0, /*tp_setattro*/
  0, /*tp_as_buffer*/
  Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
  "\n    cKalmanFilter(model, filter=FILTER_CONVENTIONAL, inversion_method=INVERT_UNIVARIATE | SOLVE_CHOLESKY, stability_method=STABILITY_FORCE_SYMMETRY, tolerance=1e-19)\n\n    A representation of the Kalman filter recursions.\n\n    While the filter is mathematically represented as a recursion, it is here\n    translated into Python as a stateful iterator.\n\n    Because there are actually several types of Kalman filter depending on the\n    state space model of interest, this class only handles the *iteration*\n    aspect of filtering, and delegates the actual operations to four general\n    workhorse routines, which can be implemented separately for each type of\n    Kalman filter.\n\n    In order to maintain a consistent interface, and because these four general\n    routines may be quite different across filter types, their argument is only\n    the stateful ?KalmanFilter object. Furthermore, in order to allow the\n    different types of filter to substitute alternate matrices, this class\n    defines a set of pointers to the various state space arrays and the\n    filtering output arrays.\n\n    For example, handling missing observations requires not only substituting\n    `obs`, `design`, and `obs_cov` matrices, but the new matrices actually have\n    different dimensions than the originals. This can be flexibly accomodated\n    simply by replacing e.g. the `obs` pointer to the substituted `obs` array\n    and replacing `k_endog` for that iteration. Then in the next iteration, when\n    the `obs` vector may be missing different elements (or none at all), it can\n    again be redefined.\n\n    Each iteration of the filter (see `__next__`) proceeds in a number of\n    steps.\n\n    `initialize_object_pointers` initializes pointers to current-iteration\n    objects (i.e. the state space arrays and filter output arrays).  \n\n    `initialize_function_pointers` initializes pointers to the appropriate\n    Kalman filtering routines (i.e. `forecast_conventional` or\n    `forecast_exact_initial`, etc.).  \n\n    `select_arrays` converts the base arrays into \"selected\" arrays using\n    selection matrices. In particular, it handles the state covariance matrix\n    and redefined matrices based on missing values.  \n\n    `post_convergence` handles copying arrays from time $t-1$ to time $t$ when\n    the Kalman filter has converged and they don't need to be re-calculated.  \n\n    `forecasting` calls the Kalman filter `forcasting_<filter type>` routine\n\n    `inversion` calls the appropriate function to invert the forecast error\n    covariance matrix.  \n\n    `updating` calls the Kalman filter `updating_<filter type>` routine\n\n    `loglikelihood` calls the Kalman filter `loglikelihood_<filter type>` routine\n\n    `prediction` calls the Kalman filter `prediction_<filter type>` routine\n\n    `numerical_stability` performs end-of-iteration tasks to improve the numerical\n    stability of the filter \n\n    `check_convergence` checks for convergence of the filter to steady-state.\n    ", /*tp_doc*/
  __pyx_tp_traverse_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter, /*tp_traverse*/
  __pyx_tp_clear_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter, /*tp_clear*/
  0, /*tp_richcompare*/
  0, /*tp_weaklistoffset*/
  __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_7__iter__, /*tp_iter*/
  __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_11__next__, /*tp_iternext*/
  __pyx_methods_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter, /*tp_methods*/
  0, /*tp_members*/
  __pyx_getsets_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter, /*tp_getset*/
  0, /*tp_base*/
  0, /*tp_dict*/
  0, /*tp_descr_get*/
  0, /*tp_descr_set*/
  0, /*tp_dictoffset*/
  __pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_1__init__, /*tp_init*/
  0, /*tp_alloc*/
  __pyx_tp_new_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter, /*tp_new*/
  0, /*tp_free*/
  0, /*tp_is_gc*/
  0, /*tp_bases*/
  0, /*tp_mro*/
  0, /*tp_cache*/
  0, /*tp_subclasses*/
  0, /*tp_weaklist*/
  0, /*tp_del*/
  0, /*tp_version_tag*/
  #if PY_VERSION_HEX >= 0x030400a1
  0, /*tp_finalize*/
  #endif
};

static PyObject *__pyx_tp_new_array(PyTypeObject *t, PyObject *a, PyObject *k) {
  struct __pyx_array_obj *p;
  PyObject *o;
  if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
    o = (*t->tp_alloc)(t, 0);
  } else {
    o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
  }
  if (unlikely(!o)) return 0;
  p = ((struct __pyx_array_obj *)o);
  p->mode = ((PyObject*)Py_None); Py_INCREF(Py_None);
  p->_format = ((PyObject*)Py_None); Py_INCREF(Py_None);
  if (unlikely(__pyx_array___cinit__(o, a, k) < 0)) {
    Py_DECREF(o); o = 0;
  }
  return o;
}

static void __pyx_tp_dealloc_array(PyObject *o) {
  struct __pyx_array_obj *p = (struct __pyx_array_obj *)o;
  #if PY_VERSION_HEX >= 0x030400a1
  if (unlikely(Py_TYPE(o)->tp_finalize) && (!PyType_IS_GC(Py_TYPE(o)) || !_PyGC_FINALIZED(o))) {
    if (PyObject_CallFinalizerFromDealloc(o)) return;
  }
  #endif
  {
    PyObject *etype, *eval, *etb;
    PyErr_Fetch(&etype, &eval, &etb);
    ++Py_REFCNT(o);
    __pyx_array___dealloc__(o);
    --Py_REFCNT(o);
    PyErr_Restore(etype, eval, etb);
  }
  Py_CLEAR(p->mode);
  Py_CLEAR(p->_format);
  (*Py_TYPE(o)->tp_free)(o);
}
static PyObject *__pyx_sq_item_array(PyObject *o, Py_ssize_t i) {
  PyObject *r;
  PyObject *x = PyInt_FromSsize_t(i); if(!x) return 0;
  r = Py_TYPE(o)->tp_as_mapping->mp_subscript(o, x);
  Py_DECREF(x);
  return r;
}

static int __pyx_mp_ass_subscript_array(PyObject *o, PyObject *i, PyObject *v) {
  if (v) {
    return __pyx_array___setitem__(o, i, v);
  }
  else {
    PyErr_Format(PyExc_NotImplementedError,
      "Subscript deletion not supported by %.200s", Py_TYPE(o)->tp_name);
    return -1;
  }
}

static PyObject *__pyx_tp_getattro_array(PyObject *o, PyObject *n) {
  PyObject *v = PyObject_GenericGetAttr(o, n);
  if (!v && PyErr_ExceptionMatches(PyExc_AttributeError)) {
    PyErr_Clear();
    v = __pyx_array___getattr__(o, n);
  }
  return v;
}

static PyObject *__pyx_getprop___pyx_array_memview(PyObject *o, CYTHON_UNUSED void *x) {
  return get_memview(o);
}

static PyMethodDef __pyx_methods_array[] = {
  {"__getattr__", (PyCFunction)__pyx_array___getattr__, METH_O|METH_COEXIST, 0},
  {0, 0, 0, 0}
};

static struct PyGetSetDef __pyx_getsets_array[] = {
  {(char *)"memview", __pyx_getprop___pyx_array_memview, 0, 0, 0},
  {0, 0, 0, 0, 0}
};

static PySequenceMethods __pyx_tp_as_sequence_array = {
  0, /*sq_length*/
  0, /*sq_concat*/
  0, /*sq_repeat*/
  __pyx_sq_item_array, /*sq_item*/
  0, /*sq_slice*/
  0, /*sq_ass_item*/
  0, /*sq_ass_slice*/
  0, /*sq_contains*/
  0, /*sq_inplace_concat*/
  0, /*sq_inplace_repeat*/
};

static PyMappingMethods __pyx_tp_as_mapping_array = {
  0, /*mp_length*/
  __pyx_array___getitem__, /*mp_subscript*/
  __pyx_mp_ass_subscript_array, /*mp_ass_subscript*/
};

static PyBufferProcs __pyx_tp_as_buffer_array = {
  #if PY_MAJOR_VERSION < 3
  0, /*bf_getreadbuffer*/
  #endif
  #if PY_MAJOR_VERSION < 3
  0, /*bf_getwritebuffer*/
  #endif
  #if PY_MAJOR_VERSION < 3
  0, /*bf_getsegcount*/
  #endif
  #if PY_MAJOR_VERSION < 3
  0, /*bf_getcharbuffer*/
  #endif
  __pyx_array_getbuffer, /*bf_getbuffer*/
  0, /*bf_releasebuffer*/
};

static PyTypeObject __pyx_type___pyx_array = {
  PyVarObject_HEAD_INIT(0, 0)
  "statsmodels.tsa.statespace._statespace.array", /*tp_name*/
  sizeof(struct __pyx_array_obj), /*tp_basicsize*/
  0, /*tp_itemsize*/
  __pyx_tp_dealloc_array, /*tp_dealloc*/
  0, /*tp_print*/
  0, /*tp_getattr*/
  0, /*tp_setattr*/
  #if PY_MAJOR_VERSION < 3
  0, /*tp_compare*/
  #else
  0, /*reserved*/
  #endif
  0, /*tp_repr*/
  0, /*tp_as_number*/
  &__pyx_tp_as_sequence_array, /*tp_as_sequence*/
  &__pyx_tp_as_mapping_array, /*tp_as_mapping*/
  0, /*tp_hash*/
  0, /*tp_call*/
  0, /*tp_str*/
  __pyx_tp_getattro_array, /*tp_getattro*/
  0, /*tp_setattro*/
  &__pyx_tp_as_buffer_array, /*tp_as_buffer*/
  Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/
  0, /*tp_doc*/
  0, /*tp_traverse*/
  0, /*tp_clear*/
  0, /*tp_richcompare*/
  0, /*tp_weaklistoffset*/
  0, /*tp_iter*/
  0, /*tp_iternext*/
  __pyx_methods_array, /*tp_methods*/
  0, /*tp_members*/
  __pyx_getsets_array, /*tp_getset*/
  0, /*tp_base*/
  0, /*tp_dict*/
  0, /*tp_descr_get*/
  0, /*tp_descr_set*/
  0, /*tp_dictoffset*/
  0, /*tp_init*/
  0, /*tp_alloc*/
  __pyx_tp_new_array, /*tp_new*/
  0, /*tp_free*/
  0, /*tp_is_gc*/
  0, /*tp_bases*/
  0, /*tp_mro*/
  0, /*tp_cache*/
  0, /*tp_subclasses*/
  0, /*tp_weaklist*/
  0, /*tp_del*/
  0, /*tp_version_tag*/
  #if PY_VERSION_HEX >= 0x030400a1
  0, /*tp_finalize*/
  #endif
};

static PyObject *__pyx_tp_new_Enum(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
  struct __pyx_MemviewEnum_obj *p;
  PyObject *o;
  if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
    o = (*t->tp_alloc)(t, 0);
  } else {
    o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
  }
  if (unlikely(!o)) return 0;
  p = ((struct __pyx_MemviewEnum_obj *)o);
  p->name = Py_None; Py_INCREF(Py_None);
  return o;
}

static void __pyx_tp_dealloc_Enum(PyObject *o) {
  struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o;
  #if PY_VERSION_HEX >= 0x030400a1
  if (unlikely(Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
    if (PyObject_CallFinalizerFromDealloc(o)) return;
  }
  #endif
  PyObject_GC_UnTrack(o);
  Py_CLEAR(p->name);
  (*Py_TYPE(o)->tp_free)(o);
}

static int __pyx_tp_traverse_Enum(PyObject *o, visitproc v, void *a) {
  int e;
  struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o;
  if (p->name) {
    e = (*v)(p->name, a); if (e) return e;
  }
  return 0;
}

static int __pyx_tp_clear_Enum(PyObject *o) {
  PyObject* tmp;
  struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o;
  tmp = ((PyObject*)p->name);
  p->name = Py_None; Py_INCREF(Py_None);
  Py_XDECREF(tmp);
  return 0;
}

static PyMethodDef __pyx_methods_Enum[] = {
  {0, 0, 0, 0}
};

static PyTypeObject __pyx_type___pyx_MemviewEnum = {
  PyVarObject_HEAD_INIT(0, 0)
  "statsmodels.tsa.statespace._statespace.Enum", /*tp_name*/
  sizeof(struct __pyx_MemviewEnum_obj), /*tp_basicsize*/
  0, /*tp_itemsize*/
  __pyx_tp_dealloc_Enum, /*tp_dealloc*/
  0, /*tp_print*/
  0, /*tp_getattr*/
  0, /*tp_setattr*/
  #if PY_MAJOR_VERSION < 3
  0, /*tp_compare*/
  #else
  0, /*reserved*/
  #endif
  __pyx_MemviewEnum___repr__, /*tp_repr*/
  0, /*tp_as_number*/
  0, /*tp_as_sequence*/
  0, /*tp_as_mapping*/
  0, /*tp_hash*/
  0, /*tp_call*/
  0, /*tp_str*/
  0, /*tp_getattro*/
  0, /*tp_setattro*/
  0, /*tp_as_buffer*/
  Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
  0, /*tp_doc*/
  __pyx_tp_traverse_Enum, /*tp_traverse*/
  __pyx_tp_clear_Enum, /*tp_clear*/
  0, /*tp_richcompare*/
  0, /*tp_weaklistoffset*/
  0, /*tp_iter*/
  0, /*tp_iternext*/
  __pyx_methods_Enum, /*tp_methods*/
  0, /*tp_members*/
  0, /*tp_getset*/
  0, /*tp_base*/
  0, /*tp_dict*/
  0, /*tp_descr_get*/
  0, /*tp_descr_set*/
  0, /*tp_dictoffset*/
  __pyx_MemviewEnum___init__, /*tp_init*/
  0, /*tp_alloc*/
  __pyx_tp_new_Enum, /*tp_new*/
  0, /*tp_free*/
  0, /*tp_is_gc*/
  0, /*tp_bases*/
  0, /*tp_mro*/
  0, /*tp_cache*/
  0, /*tp_subclasses*/
  0, /*tp_weaklist*/
  0, /*tp_del*/
  0, /*tp_version_tag*/
  #if PY_VERSION_HEX >= 0x030400a1
  0, /*tp_finalize*/
  #endif
};
static struct __pyx_vtabstruct_memoryview __pyx_vtable_memoryview;

static PyObject *__pyx_tp_new_memoryview(PyTypeObject *t, PyObject *a, PyObject *k) {
  struct __pyx_memoryview_obj *p;
  PyObject *o;
  if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
    o = (*t->tp_alloc)(t, 0);
  } else {
    o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
  }
  if (unlikely(!o)) return 0;
  p = ((struct __pyx_memoryview_obj *)o);
  p->__pyx_vtab = __pyx_vtabptr_memoryview;
  p->obj = Py_None; Py_INCREF(Py_None);
  p->_size = Py_None; Py_INCREF(Py_None);
  p->_array_interface = Py_None; Py_INCREF(Py_None);
  p->view.obj = NULL;
  if (unlikely(__pyx_memoryview___cinit__(o, a, k) < 0)) {
    Py_DECREF(o); o = 0;
  }
  return o;
}

static void __pyx_tp_dealloc_memoryview(PyObject *o) {
  struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o;
  #if PY_VERSION_HEX >= 0x030400a1
  if (unlikely(Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
    if (PyObject_CallFinalizerFromDealloc(o)) return;
  }
  #endif
  PyObject_GC_UnTrack(o);
  {
    PyObject *etype, *eval, *etb;
    PyErr_Fetch(&etype, &eval, &etb);
    ++Py_REFCNT(o);
    __pyx_memoryview___dealloc__(o);
    --Py_REFCNT(o);
    PyErr_Restore(etype, eval, etb);
  }
  Py_CLEAR(p->obj);
  Py_CLEAR(p->_size);
  Py_CLEAR(p->_array_interface);
  (*Py_TYPE(o)->tp_free)(o);
}

static int __pyx_tp_traverse_memoryview(PyObject *o, visitproc v, void *a) {
  int e;
  struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o;
  if (p->obj) {
    e = (*v)(p->obj, a); if (e) return e;
  }
  if (p->_size) {
    e = (*v)(p->_size, a); if (e) return e;
  }
  if (p->_array_interface) {
    e = (*v)(p->_array_interface, a); if (e) return e;
  }
  if (p->view.obj) {
    e = (*v)(p->view.obj, a); if (e) return e;
  }
  return 0;
}

static int __pyx_tp_clear_memoryview(PyObject *o) {
  PyObject* tmp;
  struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o;
  tmp = ((PyObject*)p->obj);
  p->obj = Py_None; Py_INCREF(Py_None);
  Py_XDECREF(tmp);
  tmp = ((PyObject*)p->_size);
  p->_size = Py_None; Py_INCREF(Py_None);
  Py_XDECREF(tmp);
  tmp = ((PyObject*)p->_array_interface);
  p->_array_interface = Py_None; Py_INCREF(Py_None);
  Py_XDECREF(tmp);
  Py_CLEAR(p->view.obj);
  return 0;
}
static PyObject *__pyx_sq_item_memoryview(PyObject *o, Py_ssize_t i) {
  PyObject *r;
  PyObject *x = PyInt_FromSsize_t(i); if(!x) return 0;
  r = Py_TYPE(o)->tp_as_mapping->mp_subscript(o, x);
  Py_DECREF(x);
  return r;
}

static int __pyx_mp_ass_subscript_memoryview(PyObject *o, PyObject *i, PyObject *v) {
  if (v) {
    return __pyx_memoryview___setitem__(o, i, v);
  }
  else {
    PyErr_Format(PyExc_NotImplementedError,
      "Subscript deletion not supported by %.200s", Py_TYPE(o)->tp_name);
    return -1;
  }
}

static PyObject *__pyx_getprop___pyx_memoryview_T(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_memoryview_transpose(o);
}

static PyObject *__pyx_getprop___pyx_memoryview_base(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_memoryview__get__base(o);
}

static PyObject *__pyx_getprop___pyx_memoryview_shape(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_memoryview_get_shape(o);
}

static PyObject *__pyx_getprop___pyx_memoryview_strides(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_memoryview_get_strides(o);
}

static PyObject *__pyx_getprop___pyx_memoryview_suboffsets(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_memoryview_get_suboffsets(o);
}

static PyObject *__pyx_getprop___pyx_memoryview_ndim(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_memoryview_get_ndim(o);
}

static PyObject *__pyx_getprop___pyx_memoryview_itemsize(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_memoryview_get_itemsize(o);
}

static PyObject *__pyx_getprop___pyx_memoryview_nbytes(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_memoryview_get_nbytes(o);
}

static PyObject *__pyx_getprop___pyx_memoryview_size(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_memoryview_get_size(o);
}

static PyMethodDef __pyx_methods_memoryview[] = {
  {"is_c_contig", (PyCFunction)__pyx_memoryview_is_c_contig, METH_NOARGS, 0},
  {"is_f_contig", (PyCFunction)__pyx_memoryview_is_f_contig, METH_NOARGS, 0},
  {"copy", (PyCFunction)__pyx_memoryview_copy, METH_NOARGS, 0},
  {"copy_fortran", (PyCFunction)__pyx_memoryview_copy_fortran, METH_NOARGS, 0},
  {0, 0, 0, 0}
};

static struct PyGetSetDef __pyx_getsets_memoryview[] = {
  {(char *)"T", __pyx_getprop___pyx_memoryview_T, 0, 0, 0},
  {(char *)"base", __pyx_getprop___pyx_memoryview_base, 0, 0, 0},
  {(char *)"shape", __pyx_getprop___pyx_memoryview_shape, 0, 0, 0},
  {(char *)"strides", __pyx_getprop___pyx_memoryview_strides, 0, 0, 0},
  {(char *)"suboffsets", __pyx_getprop___pyx_memoryview_suboffsets, 0, 0, 0},
  {(char *)"ndim", __pyx_getprop___pyx_memoryview_ndim, 0, 0, 0},
  {(char *)"itemsize", __pyx_getprop___pyx_memoryview_itemsize, 0, 0, 0},
  {(char *)"nbytes", __pyx_getprop___pyx_memoryview_nbytes, 0, 0, 0},
  {(char *)"size", __pyx_getprop___pyx_memoryview_size, 0, 0, 0},
  {0, 0, 0, 0, 0}
};

static PySequenceMethods __pyx_tp_as_sequence_memoryview = {
  __pyx_memoryview___len__, /*sq_length*/
  0, /*sq_concat*/
  0, /*sq_repeat*/
  __pyx_sq_item_memoryview, /*sq_item*/
  0, /*sq_slice*/
  0, /*sq_ass_item*/
  0, /*sq_ass_slice*/
  0, /*sq_contains*/
  0, /*sq_inplace_concat*/
  0, /*sq_inplace_repeat*/
};

static PyMappingMethods __pyx_tp_as_mapping_memoryview = {
  __pyx_memoryview___len__, /*mp_length*/
  __pyx_memoryview___getitem__, /*mp_subscript*/
  __pyx_mp_ass_subscript_memoryview, /*mp_ass_subscript*/
};

static PyBufferProcs __pyx_tp_as_buffer_memoryview = {
  #if PY_MAJOR_VERSION < 3
  0, /*bf_getreadbuffer*/
  #endif
  #if PY_MAJOR_VERSION < 3
  0, /*bf_getwritebuffer*/
  #endif
  #if PY_MAJOR_VERSION < 3
  0, /*bf_getsegcount*/
  #endif
  #if PY_MAJOR_VERSION < 3
  0, /*bf_getcharbuffer*/
  #endif
  __pyx_memoryview_getbuffer, /*bf_getbuffer*/
  0, /*bf_releasebuffer*/
};

static PyTypeObject __pyx_type___pyx_memoryview = {
  PyVarObject_HEAD_INIT(0, 0)
  "statsmodels.tsa.statespace._statespace.memoryview", /*tp_name*/
  sizeof(struct __pyx_memoryview_obj), /*tp_basicsize*/
  0, /*tp_itemsize*/
  __pyx_tp_dealloc_memoryview, /*tp_dealloc*/
  0, /*tp_print*/
  0, /*tp_getattr*/
  0, /*tp_setattr*/
  #if PY_MAJOR_VERSION < 3
  0, /*tp_compare*/
  #else
  0, /*reserved*/
  #endif
  __pyx_memoryview___repr__, /*tp_repr*/
  0, /*tp_as_number*/
  &__pyx_tp_as_sequence_memoryview, /*tp_as_sequence*/
  &__pyx_tp_as_mapping_memoryview, /*tp_as_mapping*/
  0, /*tp_hash*/
  0, /*tp_call*/
  __pyx_memoryview___str__, /*tp_str*/
  0, /*tp_getattro*/
  0, /*tp_setattro*/
  &__pyx_tp_as_buffer_memoryview, /*tp_as_buffer*/
  Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
  0, /*tp_doc*/
  __pyx_tp_traverse_memoryview, /*tp_traverse*/
  __pyx_tp_clear_memoryview, /*tp_clear*/
  0, /*tp_richcompare*/
  0, /*tp_weaklistoffset*/
  0, /*tp_iter*/
  0, /*tp_iternext*/
  __pyx_methods_memoryview, /*tp_methods*/
  0, /*tp_members*/
  __pyx_getsets_memoryview, /*tp_getset*/
  0, /*tp_base*/
  0, /*tp_dict*/
  0, /*tp_descr_get*/
  0, /*tp_descr_set*/
  0, /*tp_dictoffset*/
  0, /*tp_init*/
  0, /*tp_alloc*/
  __pyx_tp_new_memoryview, /*tp_new*/
  0, /*tp_free*/
  0, /*tp_is_gc*/
  0, /*tp_bases*/
  0, /*tp_mro*/
  0, /*tp_cache*/
  0, /*tp_subclasses*/
  0, /*tp_weaklist*/
  0, /*tp_del*/
  0, /*tp_version_tag*/
  #if PY_VERSION_HEX >= 0x030400a1
  0, /*tp_finalize*/
  #endif
};
static struct __pyx_vtabstruct__memoryviewslice __pyx_vtable__memoryviewslice;

static PyObject *__pyx_tp_new__memoryviewslice(PyTypeObject *t, PyObject *a, PyObject *k) {
  struct __pyx_memoryviewslice_obj *p;
  PyObject *o = __pyx_tp_new_memoryview(t, a, k);
  if (unlikely(!o)) return 0;
  p = ((struct __pyx_memoryviewslice_obj *)o);
  p->__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_memoryview*)__pyx_vtabptr__memoryviewslice;
  p->from_object = Py_None; Py_INCREF(Py_None);
  p->from_slice.memview = NULL;
  return o;
}

static void __pyx_tp_dealloc__memoryviewslice(PyObject *o) {
  struct __pyx_memoryviewslice_obj *p = (struct __pyx_memoryviewslice_obj *)o;
  #if PY_VERSION_HEX >= 0x030400a1
  if (unlikely(Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
    if (PyObject_CallFinalizerFromDealloc(o)) return;
  }
  #endif
  PyObject_GC_UnTrack(o);
  {
    PyObject *etype, *eval, *etb;
    PyErr_Fetch(&etype, &eval, &etb);
    ++Py_REFCNT(o);
    __pyx_memoryviewslice___dealloc__(o);
    --Py_REFCNT(o);
    PyErr_Restore(etype, eval, etb);
  }
  Py_CLEAR(p->from_object);
  PyObject_GC_Track(o);
  __pyx_tp_dealloc_memoryview(o);
}

static int __pyx_tp_traverse__memoryviewslice(PyObject *o, visitproc v, void *a) {
  int e;
  struct __pyx_memoryviewslice_obj *p = (struct __pyx_memoryviewslice_obj *)o;
  e = __pyx_tp_traverse_memoryview(o, v, a); if (e) return e;
  if (p->from_object) {
    e = (*v)(p->from_object, a); if (e) return e;
  }
  return 0;
}

static int __pyx_tp_clear__memoryviewslice(PyObject *o) {
  PyObject* tmp;
  struct __pyx_memoryviewslice_obj *p = (struct __pyx_memoryviewslice_obj *)o;
  __pyx_tp_clear_memoryview(o);
  tmp = ((PyObject*)p->from_object);
  p->from_object = Py_None; Py_INCREF(Py_None);
  Py_XDECREF(tmp);
  __PYX_XDEC_MEMVIEW(&p->from_slice, 1);
  return 0;
}

static PyObject *__pyx_getprop___pyx_memoryviewslice_base(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_memoryviewslice__get__base(o);
}

static PyMethodDef __pyx_methods__memoryviewslice[] = {
  {0, 0, 0, 0}
};

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};

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  0, /*tp_hash*/
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  0, /*tp_getattro*/
  0, /*tp_setattro*/
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  "Internal class for passing memoryview slices to Python", /*tp_doc*/
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  0, /*tp_weaklistoffset*/
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  0, /*tp_iternext*/
  __pyx_methods__memoryviewslice, /*tp_methods*/
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  __pyx_getsets__memoryviewslice, /*tp_getset*/
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};

static PyMethodDef __pyx_methods[] = {
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  {"_dcompute_coefficients_from_multivariate_pacf", (PyCFunction)__pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_9_dcompute_coefficients_from_multivariate_pacf, METH_VARARGS|METH_KEYWORDS, __pyx_doc_11statsmodels_3tsa_10statespace_11_statespace_8_dcompute_coefficients_from_multivariate_pacf},
  {"_dconstrain_sv_less_than_one", (PyCFunction)__pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_11_dconstrain_sv_less_than_one, METH_VARARGS|METH_KEYWORDS, __pyx_doc_11statsmodels_3tsa_10statespace_11_statespace_10_dconstrain_sv_less_than_one},
  {"_ccompute_coefficients_from_multivariate_pacf", (PyCFunction)__pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_13_ccompute_coefficients_from_multivariate_pacf, METH_VARARGS|METH_KEYWORDS, __pyx_doc_11statsmodels_3tsa_10statespace_11_statespace_12_ccompute_coefficients_from_multivariate_pacf},
  {"_cconstrain_sv_less_than_one", (PyCFunction)__pyx_pw_11statsmodels_3tsa_10statespace_11_statespace_15_cconstrain_sv_less_than_one, METH_VARARGS|METH_KEYWORDS, __pyx_doc_11statsmodels_3tsa_10statespace_11_statespace_14_cconstrain_sv_less_than_one},
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};

#if PY_MAJOR_VERSION >= 3
static struct PyModuleDef __pyx_moduledef = {
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    NULL, /* m_clear */
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};
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  __pyx_vtable_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter.set_filter_method = (PyObject *(*)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *, int, int __pyx_skip_dispatch, struct __pyx_opt_args_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_set_filter_method *__pyx_optional_args))__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_set_filter_method;
  __pyx_vtable_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter.seek = (PyObject *(*)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *, unsigned int, int __pyx_skip_dispatch, struct __pyx_opt_args_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_seek *__pyx_optional_args))__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_seek;
  __pyx_vtable_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter.initialize_statespace_object_pointers = (PyObject *(*)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *, int __pyx_skip_dispatch))__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_initialize_statespace_object_pointers;
  __pyx_vtable_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter.initialize_filter_object_pointers = (PyObject *(*)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *, int __pyx_skip_dispatch))__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_initialize_filter_object_pointers;
  __pyx_vtable_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter.initialize_function_pointers = (void (*)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *))__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_initialize_function_pointers;
  __pyx_vtable_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter.select_state_cov = (void (*)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *))__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_select_state_cov;
  __pyx_vtable_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter.select_missing = (PyObject *(*)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *, int __pyx_skip_dispatch))__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_select_missing;
  __pyx_vtable_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter._select_missing_entire_obs = (void (*)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *))__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter__select_missing_entire_obs;
  __pyx_vtable_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter._select_missing_partial_obs = (void (*)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *))__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter__select_missing_partial_obs;
  __pyx_vtable_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter.post_convergence = (void (*)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *))__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_post_convergence;
  __pyx_vtable_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter.numerical_stability = (void (*)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *))__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_numerical_stability;
  __pyx_vtable_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter.check_convergence = (void (*)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *))__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_check_convergence;
  __pyx_vtable_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter.migrate_storage = (void (*)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter *))__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_migrate_storage;
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  {
    PyObject *wrapper = PyObject_GetAttrString((PyObject *)&__pyx_type_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter, "__next__"); if (unlikely(!wrapper)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 4840; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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      ((PyWrapperDescrObject *)wrapper)->d_base = &__pyx_wrapperbase_11statsmodels_3tsa_10statespace_11_statespace_13dKalmanFilter_10__next__;
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  if (__Pyx_SetVtable(__pyx_type_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter.tp_dict, __pyx_vtabptr_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 4840; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
  if (PyObject_SetAttrString(__pyx_m, "dKalmanFilter", (PyObject *)&__pyx_type_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 4840; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
  __pyx_ptype_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter = &__pyx_type_11statsmodels_3tsa_10statespace_11_statespace_dKalmanFilter;
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  __pyx_type_11statsmodels_3tsa_10statespace_11_statespace_cStatespace.tp_print = 0;
  if (PyObject_SetAttrString(__pyx_m, "cStatespace", (PyObject *)&__pyx_type_11statsmodels_3tsa_10statespace_11_statespace_cStatespace) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 5979; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
  __pyx_ptype_11statsmodels_3tsa_10statespace_11_statespace_cStatespace = &__pyx_type_11statsmodels_3tsa_10statespace_11_statespace_cStatespace;
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  __pyx_vtable_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter.seek = (PyObject *(*)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *, unsigned int, int __pyx_skip_dispatch, struct __pyx_opt_args_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_seek *__pyx_optional_args))__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_seek;
  __pyx_vtable_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter.initialize_statespace_object_pointers = (PyObject *(*)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *, int __pyx_skip_dispatch))__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_initialize_statespace_object_pointers;
  __pyx_vtable_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter.initialize_filter_object_pointers = (PyObject *(*)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *, int __pyx_skip_dispatch))__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_initialize_filter_object_pointers;
  __pyx_vtable_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter.initialize_function_pointers = (void (*)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *))__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_initialize_function_pointers;
  __pyx_vtable_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter.select_state_cov = (void (*)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *))__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_select_state_cov;
  __pyx_vtable_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter.select_missing = (PyObject *(*)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *, int __pyx_skip_dispatch))__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_select_missing;
  __pyx_vtable_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter._select_missing_entire_obs = (void (*)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *))__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter__select_missing_entire_obs;
  __pyx_vtable_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter._select_missing_partial_obs = (void (*)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *))__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter__select_missing_partial_obs;
  __pyx_vtable_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter.post_convergence = (void (*)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *))__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_post_convergence;
  __pyx_vtable_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter.numerical_stability = (void (*)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *))__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_numerical_stability;
  __pyx_vtable_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter.check_convergence = (void (*)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *))__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_check_convergence;
  __pyx_vtable_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter.migrate_storage = (void (*)(struct __pyx_obj_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter *))__pyx_f_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_migrate_storage;
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  __pyx_type_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter.tp_print = 0;
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  {
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    if (Py_TYPE(wrapper) == &PyWrapperDescr_Type) {
      __pyx_wrapperbase_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_8__call__ = *((PyWrapperDescrObject *)wrapper)->d_base;
      __pyx_wrapperbase_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_8__call__.doc = __pyx_doc_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_8__call__;
      ((PyWrapperDescrObject *)wrapper)->d_base = &__pyx_wrapperbase_11statsmodels_3tsa_10statespace_11_statespace_13cKalmanFilter_8__call__;
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  {
    PyObject *wrapper = PyObject_GetAttrString((PyObject *)&__pyx_type_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter, "__next__"); if (unlikely(!wrapper)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 6777; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
    if (Py_TYPE(wrapper) == &PyWrapperDescr_Type) {
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  __pyx_ptype_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter = &__pyx_type_11statsmodels_3tsa_10statespace_11_statespace_cKalmanFilter;
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  /*--- Variable import code ---*/
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  /* "statsmodels\tsa\statespace\_statespace.pyx":15
 * # ### Filters
 * # TODO note that only the conventional filter is implemented
 * cdef int FILTER_CONVENTIONAL = 0x01     # Durbin and Koopman (2012), Chapter 4             # <<<<<<<<<<<<<<
 * cdef int FILTER_EXACT_INITIAL = 0x02    # ibid., Chapter 5.6
 * cdef int FILTER_AUGMENTED = 0x04        # ibid., Chapter 5.7
 */
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 * # TODO note that only the conventional filter is implemented
 * cdef int FILTER_CONVENTIONAL = 0x01     # Durbin and Koopman (2012), Chapter 4
 * cdef int FILTER_EXACT_INITIAL = 0x02    # ibid., Chapter 5.6             # <<<<<<<<<<<<<<
 * cdef int FILTER_AUGMENTED = 0x04        # ibid., Chapter 5.7
 * cdef int FILTER_SQUARE_ROOT = 0x08      # ibid., Chapter 6.3
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 * cdef int FILTER_CONVENTIONAL = 0x01     # Durbin and Koopman (2012), Chapter 4
 * cdef int FILTER_EXACT_INITIAL = 0x02    # ibid., Chapter 5.6
 * cdef int FILTER_AUGMENTED = 0x04        # ibid., Chapter 5.7             # <<<<<<<<<<<<<<
 * cdef int FILTER_SQUARE_ROOT = 0x08      # ibid., Chapter 6.3
 * cdef int FILTER_UNIVARIATE = 0x10       # ibid., Chapter 6.4
 */
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 * cdef int FILTER_EXACT_INITIAL = 0x02    # ibid., Chapter 5.6
 * cdef int FILTER_AUGMENTED = 0x04        # ibid., Chapter 5.7
 * cdef int FILTER_SQUARE_ROOT = 0x08      # ibid., Chapter 6.3             # <<<<<<<<<<<<<<
 * cdef int FILTER_UNIVARIATE = 0x10       # ibid., Chapter 6.4
 * cdef int FILTER_COLLAPSED = 0x20        # ibid., Chapter 6.5
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 * cdef int FILTER_AUGMENTED = 0x04        # ibid., Chapter 5.7
 * cdef int FILTER_SQUARE_ROOT = 0x08      # ibid., Chapter 6.3
 * cdef int FILTER_UNIVARIATE = 0x10       # ibid., Chapter 6.4             # <<<<<<<<<<<<<<
 * cdef int FILTER_COLLAPSED = 0x20        # ibid., Chapter 6.5
 * cdef int FILTER_EXTENDED = 0x40         # ibid., Chapter 10.2
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 * cdef int FILTER_SQUARE_ROOT = 0x08      # ibid., Chapter 6.3
 * cdef int FILTER_UNIVARIATE = 0x10       # ibid., Chapter 6.4
 * cdef int FILTER_COLLAPSED = 0x20        # ibid., Chapter 6.5             # <<<<<<<<<<<<<<
 * cdef int FILTER_EXTENDED = 0x40         # ibid., Chapter 10.2
 * cdef int FILTER_UNSCENTED = 0x80        # ibid., Chapter 10.3
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 * cdef int FILTER_UNIVARIATE = 0x10       # ibid., Chapter 6.4
 * cdef int FILTER_COLLAPSED = 0x20        # ibid., Chapter 6.5
 * cdef int FILTER_EXTENDED = 0x40         # ibid., Chapter 10.2             # <<<<<<<<<<<<<<
 * cdef int FILTER_UNSCENTED = 0x80        # ibid., Chapter 10.3
 * 
 */
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 * cdef int FILTER_COLLAPSED = 0x20        # ibid., Chapter 6.5
 * cdef int FILTER_EXTENDED = 0x40         # ibid., Chapter 10.2
 * cdef int FILTER_UNSCENTED = 0x80        # ibid., Chapter 10.3             # <<<<<<<<<<<<<<
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 * # Methods by which the terms using the inverse of the forecast error
 * # covariance matrix are solved.
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 * # covariance matrix are solved.
 * cdef int INVERT_UNIVARIATE = 0x01
 * cdef int SOLVE_LU = 0x02             # <<<<<<<<<<<<<<
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 * cdef int INVERT_UNIVARIATE = 0x01
 * cdef int SOLVE_LU = 0x02
 * cdef int INVERT_LU = 0x04             # <<<<<<<<<<<<<<
 * cdef int SOLVE_CHOLESKY = 0x08
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 * cdef int SOLVE_LU = 0x02
 * cdef int INVERT_LU = 0x04
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 * cdef int INVERT_CHOLESKY = 0x10
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 * cdef int INVERT_LU = 0x04
 * cdef int SOLVE_CHOLESKY = 0x08
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 * # ### Numerical Stability methods
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 * # ### Memory conservation options
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 * 
 * # ### Memory conservation options
 * cdef int MEMORY_STORE_ALL = 0             # <<<<<<<<<<<<<<
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 * cdef int MEMORY_NO_PREDICTED = 0x02
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 * # ### Memory conservation options
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 * cdef int MEMORY_NO_FORECAST = 0x01             # <<<<<<<<<<<<<<
 * cdef int MEMORY_NO_PREDICTED = 0x02
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 * cdef int MEMORY_STORE_ALL = 0
 * cdef int MEMORY_NO_FORECAST = 0x01
 * cdef int MEMORY_NO_PREDICTED = 0x02             # <<<<<<<<<<<<<<
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 * cdef int MEMORY_NO_FORECAST = 0x01
 * cdef int MEMORY_NO_PREDICTED = 0x02
 * cdef int MEMORY_NO_FILTERED = 0x04             # <<<<<<<<<<<<<<
 * cdef int MEMORY_NO_LIKELIHOOD = 0x08
 * cdef int MEMORY_CONSERVE = (
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 * cdef int MEMORY_NO_PREDICTED = 0x02
 * cdef int MEMORY_NO_FILTERED = 0x04
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 * cdef int MEMORY_CONSERVE = (
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 * cdef int MEMORY_NO_LIKELIHOOD = 0x08
 * cdef int MEMORY_CONSERVE = (
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 * try:             # <<<<<<<<<<<<<<
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    Py_ssize_t num_max,
    Py_ssize_t num_found)
{
    Py_ssize_t num_expected;
    const char *more_or_less;
    if (num_found < num_min) {
        num_expected = num_min;
        more_or_less = "at least";
    } else {
        num_expected = num_max;
        more_or_less = "at most";
    }
    if (exact) {
        more_or_less = "exactly";
    }
    PyErr_Format(PyExc_TypeError,
                 "%.200s() takes %.8s %" CYTHON_FORMAT_SSIZE_T "d positional argument%.1s (%" CYTHON_FORMAT_SSIZE_T "d given)",
                 func_name, more_or_less, num_expected,
                 (num_expected == 1) ? "" : "s", num_found);
}

static void __Pyx_RaiseDoubleKeywordsError(
    const char* func_name,
    PyObject* kw_name)
{
    PyErr_Format(PyExc_TypeError,
        #if PY_MAJOR_VERSION >= 3
        "%s() got multiple values for keyword argument '%U'", func_name, kw_name);
        #else
        "%s() got multiple values for keyword argument '%s'", func_name,
        PyString_AsString(kw_name));
        #endif
}

static int __Pyx_ParseOptionalKeywords(
    PyObject *kwds,
    PyObject **argnames[],
    PyObject *kwds2,
    PyObject *values[],
    Py_ssize_t num_pos_args,
    const char* function_name)
{
    PyObject *key = 0, *value = 0;
    Py_ssize_t pos = 0;
    PyObject*** name;
    PyObject*** first_kw_arg = argnames + num_pos_args;
    while (PyDict_Next(kwds, &pos, &key, &value)) {
        name = first_kw_arg;
        while (*name && (**name != key)) name++;
        if (*name) {
            values[name-argnames] = value;
            continue;
        }
        name = first_kw_arg;
        #if PY_MAJOR_VERSION < 3
        if (likely(PyString_CheckExact(key)) || likely(PyString_Check(key))) {
            while (*name) {
                if ((CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**name) == PyString_GET_SIZE(key))
                        && _PyString_Eq(**name, key)) {
                    values[name-argnames] = value;
                    break;
                }
                name++;
            }
            if (*name) continue;
            else {
                PyObject*** argname = argnames;
                while (argname != first_kw_arg) {
                    if ((**argname == key) || (
                            (CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**argname) == PyString_GET_SIZE(key))
                             && _PyString_Eq(**argname, key))) {
                        goto arg_passed_twice;
                    }
                    argname++;
                }
            }
        } else
        #endif
        if (likely(PyUnicode_Check(key))) {
            while (*name) {
                int cmp = (**name == key) ? 0 :
                #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3
                    (PyUnicode_GET_SIZE(**name) != PyUnicode_GET_SIZE(key)) ? 1 :
                #endif
                    PyUnicode_Compare(**name, key);
                if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad;
                if (cmp == 0) {
                    values[name-argnames] = value;
                    break;
                }
                name++;
            }
            if (*name) continue;
            else {
                PyObject*** argname = argnames;
                while (argname != first_kw_arg) {
                    int cmp = (**argname == key) ? 0 :
                    #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3
                        (PyUnicode_GET_SIZE(**argname) != PyUnicode_GET_SIZE(key)) ? 1 :
                    #endif
                        PyUnicode_Compare(**argname, key);
                    if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad;
                    if (cmp == 0) goto arg_passed_twice;
                    argname++;
                }
            }
        } else
            goto invalid_keyword_type;
        if (kwds2) {
            if (unlikely(PyDict_SetItem(kwds2, key, value))) goto bad;
        } else {
            goto invalid_keyword;
        }
    }
    return 0;
arg_passed_twice:
    __Pyx_RaiseDoubleKeywordsError(function_name, key);
    goto bad;
invalid_keyword_type:
    PyErr_Format(PyExc_TypeError,
        "%.200s() keywords must be strings", function_name);
    goto bad;
invalid_keyword:
    PyErr_Format(PyExc_TypeError,
    #if PY_MAJOR_VERSION < 3
        "%.200s() got an unexpected keyword argument '%.200s'",
        function_name, PyString_AsString(key));
    #else
        "%s() got an unexpected keyword argument '%U'",
        function_name, key);
    #endif
bad:
    return -1;
}

static CYTHON_INLINE int __Pyx_IsLittleEndian(void) {
  unsigned int n = 1;
  return *(unsigned char*)(&n) != 0;
}
static void __Pyx_BufFmt_Init(__Pyx_BufFmt_Context* ctx,
                              __Pyx_BufFmt_StackElem* stack,
                              __Pyx_TypeInfo* type) {
  stack[0].field = &ctx->root;
  stack[0].parent_offset = 0;
  ctx->root.type = type;
  ctx->root.name = "buffer dtype";
  ctx->root.offset = 0;
  ctx->head = stack;
  ctx->head->field = &ctx->root;
  ctx->fmt_offset = 0;
  ctx->head->parent_offset = 0;
  ctx->new_packmode = '@';
  ctx->enc_packmode = '@';
  ctx->new_count = 1;
  ctx->enc_count = 0;
  ctx->enc_type = 0;
  ctx->is_complex = 0;
  ctx->is_valid_array = 0;
  ctx->struct_alignment = 0;
  while (type->typegroup == 'S') {
    ++ctx->head;
    ctx->head->field = type->fields;
    ctx->head->parent_offset = 0;
    type = type->fields->type;
  }
}
static int __Pyx_BufFmt_ParseNumber(const char** ts) {
    int count;
    const char* t = *ts;
    if (*t < '0' || *t > '9') {
      return -1;
    } else {
        count = *t++ - '0';
        while (*t >= '0' && *t < '9') {
            count *= 10;
            count += *t++ - '0';
        }
    }
    *ts = t;
    return count;
}
static int __Pyx_BufFmt_ExpectNumber(const char **ts) {
    int number = __Pyx_BufFmt_ParseNumber(ts);
    if (number == -1)
        PyErr_Format(PyExc_ValueError,\
                     "Does not understand character buffer dtype format string ('%c')", **ts);
    return number;
}
static void __Pyx_BufFmt_RaiseUnexpectedChar(char ch) {
  PyErr_Format(PyExc_ValueError,
               "Unexpected format string character: '%c'", ch);
}
static const char* __Pyx_BufFmt_DescribeTypeChar(char ch, int is_complex) {
  switch (ch) {
    case 'c': return "'char'";
    case 'b': return "'signed char'";
    case 'B': return "'unsigned char'";
    case 'h': return "'short'";
    case 'H': return "'unsigned short'";
    case 'i': return "'int'";
    case 'I': return "'unsigned int'";
    case 'l': return "'long'";
    case 'L': return "'unsigned long'";
    case 'q': return "'long long'";
    case 'Q': return "'unsigned long long'";
    case 'f': return (is_complex ? "'complex float'" : "'float'");
    case 'd': return (is_complex ? "'complex double'" : "'double'");
    case 'g': return (is_complex ? "'complex long double'" : "'long double'");
    case 'T': return "a struct";
    case 'O': return "Python object";
    case 'P': return "a pointer";
    case 's': case 'p': return "a string";
    case 0: return "end";
    default: return "unparseable format string";
  }
}
static size_t __Pyx_BufFmt_TypeCharToStandardSize(char ch, int is_complex) {
  switch (ch) {
    case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1;
    case 'h': case 'H': return 2;
    case 'i': case 'I': case 'l': case 'L': return 4;
    case 'q': case 'Q': return 8;
    case 'f': return (is_complex ? 8 : 4);
    case 'd': return (is_complex ? 16 : 8);
    case 'g': {
      PyErr_SetString(PyExc_ValueError, "Python does not define a standard format string size for long double ('g')..");
      return 0;
    }
    case 'O': case 'P': return sizeof(void*);
    default:
      __Pyx_BufFmt_RaiseUnexpectedChar(ch);
      return 0;
    }
}
static size_t __Pyx_BufFmt_TypeCharToNativeSize(char ch, int is_complex) {
  switch (ch) {
    case 'c': case 'b': case 'B': case 's': case 'p': return 1;
    case 'h': case 'H': return sizeof(short);
    case 'i': case 'I': return sizeof(int);
    case 'l': case 'L': return sizeof(long);
    #ifdef HAVE_LONG_LONG
    case 'q': case 'Q': return sizeof(PY_LONG_LONG);
    #endif
    case 'f': return sizeof(float) * (is_complex ? 2 : 1);
    case 'd': return sizeof(double) * (is_complex ? 2 : 1);
    case 'g': return sizeof(long double) * (is_complex ? 2 : 1);
    case 'O': case 'P': return sizeof(void*);
    default: {
      __Pyx_BufFmt_RaiseUnexpectedChar(ch);
      return 0;
    }
  }
}
typedef struct { char c; short x; } __Pyx_st_short;
typedef struct { char c; int x; } __Pyx_st_int;
typedef struct { char c; long x; } __Pyx_st_long;
typedef struct { char c; float x; } __Pyx_st_float;
typedef struct { char c; double x; } __Pyx_st_double;
typedef struct { char c; long double x; } __Pyx_st_longdouble;
typedef struct { char c; void *x; } __Pyx_st_void_p;
#ifdef HAVE_LONG_LONG
typedef struct { char c; PY_LONG_LONG x; } __Pyx_st_longlong;
#endif
static size_t __Pyx_BufFmt_TypeCharToAlignment(char ch, CYTHON_UNUSED int is_complex) {
  switch (ch) {
    case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1;
    case 'h': case 'H': return sizeof(__Pyx_st_short) - sizeof(short);
    case 'i': case 'I': return sizeof(__Pyx_st_int) - sizeof(int);
    case 'l': case 'L': return sizeof(__Pyx_st_long) - sizeof(long);
#ifdef HAVE_LONG_LONG
    case 'q': case 'Q': return sizeof(__Pyx_st_longlong) - sizeof(PY_LONG_LONG);
#endif
    case 'f': return sizeof(__Pyx_st_float) - sizeof(float);
    case 'd': return sizeof(__Pyx_st_double) - sizeof(double);
    case 'g': return sizeof(__Pyx_st_longdouble) - sizeof(long double);
    case 'P': case 'O': return sizeof(__Pyx_st_void_p) - sizeof(void*);
    default:
      __Pyx_BufFmt_RaiseUnexpectedChar(ch);
      return 0;
    }
}
/* These are for computing the padding at the end of the struct to align
   on the first member of the struct. This will probably the same as above,
   but we don't have any guarantees.
 */
typedef struct { short x; char c; } __Pyx_pad_short;
typedef struct { int x; char c; } __Pyx_pad_int;
typedef struct { long x; char c; } __Pyx_pad_long;
typedef struct { float x; char c; } __Pyx_pad_float;
typedef struct { double x; char c; } __Pyx_pad_double;
typedef struct { long double x; char c; } __Pyx_pad_longdouble;
typedef struct { void *x; char c; } __Pyx_pad_void_p;
#ifdef HAVE_LONG_LONG
typedef struct { PY_LONG_LONG x; char c; } __Pyx_pad_longlong;
#endif
static size_t __Pyx_BufFmt_TypeCharToPadding(char ch, CYTHON_UNUSED int is_complex) {
  switch (ch) {
    case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1;
    case 'h': case 'H': return sizeof(__Pyx_pad_short) - sizeof(short);
    case 'i': case 'I': return sizeof(__Pyx_pad_int) - sizeof(int);
    case 'l': case 'L': return sizeof(__Pyx_pad_long) - sizeof(long);
#ifdef HAVE_LONG_LONG
    case 'q': case 'Q': return sizeof(__Pyx_pad_longlong) - sizeof(PY_LONG_LONG);
#endif
    case 'f': return sizeof(__Pyx_pad_float) - sizeof(float);
    case 'd': return sizeof(__Pyx_pad_double) - sizeof(double);
    case 'g': return sizeof(__Pyx_pad_longdouble) - sizeof(long double);
    case 'P': case 'O': return sizeof(__Pyx_pad_void_p) - sizeof(void*);
    default:
      __Pyx_BufFmt_RaiseUnexpectedChar(ch);
      return 0;
    }
}
static char __Pyx_BufFmt_TypeCharToGroup(char ch, int is_complex) {
  switch (ch) {
    case 'c':
        return 'H';
    case 'b': case 'h': case 'i':
    case 'l': case 'q': case 's': case 'p':
        return 'I';
    case 'B': case 'H': case 'I': case 'L': case 'Q':
        return 'U';
    case 'f': case 'd': case 'g':
        return (is_complex ? 'C' : 'R');
    case 'O':
        return 'O';
    case 'P':
        return 'P';
    default: {
      __Pyx_BufFmt_RaiseUnexpectedChar(ch);
      return 0;
    }
  }
}
static void __Pyx_BufFmt_RaiseExpected(__Pyx_BufFmt_Context* ctx) {
  if (ctx->head == NULL || ctx->head->field == &ctx->root) {
    const char* expected;
    const char* quote;
    if (ctx->head == NULL) {
      expected = "end";
      quote = "";
    } else {
      expected = ctx->head->field->type->name;
      quote = "'";
    }
    PyErr_Format(PyExc_ValueError,
                 "Buffer dtype mismatch, expected %s%s%s but got %s",
                 quote, expected, quote,
                 __Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex));
  } else {
    __Pyx_StructField* field = ctx->head->field;
    __Pyx_StructField* parent = (ctx->head - 1)->field;
    PyErr_Format(PyExc_ValueError,
                 "Buffer dtype mismatch, expected '%s' but got %s in '%s.%s'",
                 field->type->name, __Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex),
                 parent->type->name, field->name);
  }
}
static int __Pyx_BufFmt_ProcessTypeChunk(__Pyx_BufFmt_Context* ctx) {
  char group;
  size_t size, offset, arraysize = 1;
  if (ctx->enc_type == 0) return 0;
  if (ctx->head->field->type->arraysize[0]) {
    int i, ndim = 0;
    if (ctx->enc_type == 's' || ctx->enc_type == 'p') {
        ctx->is_valid_array = ctx->head->field->type->ndim == 1;
        ndim = 1;
        if (ctx->enc_count != ctx->head->field->type->arraysize[0]) {
            PyErr_Format(PyExc_ValueError,
                         "Expected a dimension of size %zu, got %zu",
                         ctx->head->field->type->arraysize[0], ctx->enc_count);
            return -1;
        }
    }
    if (!ctx->is_valid_array) {
      PyErr_Format(PyExc_ValueError, "Expected %d dimensions, got %d",
                   ctx->head->field->type->ndim, ndim);
      return -1;
    }
    for (i = 0; i < ctx->head->field->type->ndim; i++) {
      arraysize *= ctx->head->field->type->arraysize[i];
    }
    ctx->is_valid_array = 0;
    ctx->enc_count = 1;
  }
  group = __Pyx_BufFmt_TypeCharToGroup(ctx->enc_type, ctx->is_complex);
  do {
    __Pyx_StructField* field = ctx->head->field;
    __Pyx_TypeInfo* type = field->type;
    if (ctx->enc_packmode == '@' || ctx->enc_packmode == '^') {
      size = __Pyx_BufFmt_TypeCharToNativeSize(ctx->enc_type, ctx->is_complex);
    } else {
      size = __Pyx_BufFmt_TypeCharToStandardSize(ctx->enc_type, ctx->is_complex);
    }
    if (ctx->enc_packmode == '@') {
      size_t align_at = __Pyx_BufFmt_TypeCharToAlignment(ctx->enc_type, ctx->is_complex);
      size_t align_mod_offset;
      if (align_at == 0) return -1;
      align_mod_offset = ctx->fmt_offset % align_at;
      if (align_mod_offset > 0) ctx->fmt_offset += align_at - align_mod_offset;
      if (ctx->struct_alignment == 0)
          ctx->struct_alignment = __Pyx_BufFmt_TypeCharToPadding(ctx->enc_type,
                                                                 ctx->is_complex);
    }
    if (type->size != size || type->typegroup != group) {
      if (type->typegroup == 'C' && type->fields != NULL) {
        size_t parent_offset = ctx->head->parent_offset + field->offset;
        ++ctx->head;
        ctx->head->field = type->fields;
        ctx->head->parent_offset = parent_offset;
        continue;
      }
      if ((type->typegroup == 'H' || group == 'H') && type->size == size) {
      } else {
          __Pyx_BufFmt_RaiseExpected(ctx);
          return -1;
      }
    }
    offset = ctx->head->parent_offset + field->offset;
    if (ctx->fmt_offset != offset) {
      PyErr_Format(PyExc_ValueError,
                   "Buffer dtype mismatch; next field is at offset %" CYTHON_FORMAT_SSIZE_T "d but %" CYTHON_FORMAT_SSIZE_T "d expected",
                   (Py_ssize_t)ctx->fmt_offset, (Py_ssize_t)offset);
      return -1;
    }
    ctx->fmt_offset += size;
    if (arraysize)
      ctx->fmt_offset += (arraysize - 1) * size;
    --ctx->enc_count;
    while (1) {
      if (field == &ctx->root) {
        ctx->head = NULL;
        if (ctx->enc_count != 0) {
          __Pyx_BufFmt_RaiseExpected(ctx);
          return -1;
        }
        break;
      }
      ctx->head->field = ++field;
      if (field->type == NULL) {
        --ctx->head;
        field = ctx->head->field;
        continue;
      } else if (field->type->typegroup == 'S') {
        size_t parent_offset = ctx->head->parent_offset + field->offset;
        if (field->type->fields->type == NULL) continue;
        field = field->type->fields;
        ++ctx->head;
        ctx->head->field = field;
        ctx->head->parent_offset = parent_offset;
        break;
      } else {
        break;
      }
    }
  } while (ctx->enc_count);
  ctx->enc_type = 0;
  ctx->is_complex = 0;
  return 0;
}
static CYTHON_INLINE PyObject *
__pyx_buffmt_parse_array(__Pyx_BufFmt_Context* ctx, const char** tsp)
{
    const char *ts = *tsp;
    int i = 0, number;
    int ndim = ctx->head->field->type->ndim;
;
    ++ts;
    if (ctx->new_count != 1) {
        PyErr_SetString(PyExc_ValueError,
                        "Cannot handle repeated arrays in format string");
        return NULL;
    }
    if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
    while (*ts && *ts != ')') {
        switch (*ts) {
            case ' ': case '\f': case '\r': case '\n': case '\t': case '\v':  continue;
            default:  break;
        }
        number = __Pyx_BufFmt_ExpectNumber(&ts);
        if (number == -1) return NULL;
        if (i < ndim && (size_t) number != ctx->head->field->type->arraysize[i])
            return PyErr_Format(PyExc_ValueError,
                        "Expected a dimension of size %zu, got %d",
                        ctx->head->field->type->arraysize[i], number);
        if (*ts != ',' && *ts != ')')
            return PyErr_Format(PyExc_ValueError,
                                "Expected a comma in format string, got '%c'", *ts);
        if (*ts == ',') ts++;
        i++;
    }
    if (i != ndim)
        return PyErr_Format(PyExc_ValueError, "Expected %d dimension(s), got %d",
                            ctx->head->field->type->ndim, i);
    if (!*ts) {
        PyErr_SetString(PyExc_ValueError,
                        "Unexpected end of format string, expected ')'");
        return NULL;
    }
    ctx->is_valid_array = 1;
    ctx->new_count = 1;
    *tsp = ++ts;
    return Py_None;
}
static const char* __Pyx_BufFmt_CheckString(__Pyx_BufFmt_Context* ctx, const char* ts) {
  int got_Z = 0;
  while (1) {
    switch(*ts) {
      case 0:
        if (ctx->enc_type != 0 && ctx->head == NULL) {
          __Pyx_BufFmt_RaiseExpected(ctx);
          return NULL;
        }
        if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
        if (ctx->head != NULL) {
          __Pyx_BufFmt_RaiseExpected(ctx);
          return NULL;
        }
        return ts;
      case ' ':
      case '\r':
      case '\n':
        ++ts;
        break;
      case '<':
        if (!__Pyx_IsLittleEndian()) {
          PyErr_SetString(PyExc_ValueError, "Little-endian buffer not supported on big-endian compiler");
          return NULL;
        }
        ctx->new_packmode = '=';
        ++ts;
        break;
      case '>':
      case '!':
        if (__Pyx_IsLittleEndian()) {
          PyErr_SetString(PyExc_ValueError, "Big-endian buffer not supported on little-endian compiler");
          return NULL;
        }
        ctx->new_packmode = '=';
        ++ts;
        break;
      case '=':
      case '@':
      case '^':
        ctx->new_packmode = *ts++;
        break;
      case 'T':
        {
          const char* ts_after_sub;
          size_t i, struct_count = ctx->new_count;
          size_t struct_alignment = ctx->struct_alignment;
          ctx->new_count = 1;
          ++ts;
          if (*ts != '{') {
            PyErr_SetString(PyExc_ValueError, "Buffer acquisition: Expected '{' after 'T'");
            return NULL;
          }
          if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
          ctx->enc_type = 0;
          ctx->enc_count = 0;
          ctx->struct_alignment = 0;
          ++ts;
          ts_after_sub = ts;
          for (i = 0; i != struct_count; ++i) {
            ts_after_sub = __Pyx_BufFmt_CheckString(ctx, ts);
            if (!ts_after_sub) return NULL;
          }
          ts = ts_after_sub;
          if (struct_alignment) ctx->struct_alignment = struct_alignment;
        }
        break;
      case '}':
        {
          size_t alignment = ctx->struct_alignment;
          ++ts;
          if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
          ctx->enc_type = 0;
          if (alignment && ctx->fmt_offset % alignment) {
            ctx->fmt_offset += alignment - (ctx->fmt_offset % alignment);
          }
        }
        return ts;
      case 'x':
        if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
        ctx->fmt_offset += ctx->new_count;
        ctx->new_count = 1;
        ctx->enc_count = 0;
        ctx->enc_type = 0;
        ctx->enc_packmode = ctx->new_packmode;
        ++ts;
        break;
      case 'Z':
        got_Z = 1;
        ++ts;
        if (*ts != 'f' && *ts != 'd' && *ts != 'g') {
          __Pyx_BufFmt_RaiseUnexpectedChar('Z');
          return NULL;
        }
      case 'c': case 'b': case 'B': case 'h': case 'H': case 'i': case 'I':
      case 'l': case 'L': case 'q': case 'Q':
      case 'f': case 'd': case 'g':
      case 'O': case 'p':
        if (ctx->enc_type == *ts && got_Z == ctx->is_complex &&
            ctx->enc_packmode == ctx->new_packmode) {
          ctx->enc_count += ctx->new_count;
          ctx->new_count = 1;
          got_Z = 0;
          ++ts;
          break;
        }
      case 's':
        if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
        ctx->enc_count = ctx->new_count;
        ctx->enc_packmode = ctx->new_packmode;
        ctx->enc_type = *ts;
        ctx->is_complex = got_Z;
        ++ts;
        ctx->new_count = 1;
        got_Z = 0;
        break;
      case ':':
        ++ts;
        while(*ts != ':') ++ts;
        ++ts;
        break;
      case '(':
        if (!__pyx_buffmt_parse_array(ctx, &ts)) return NULL;
        break;
      default:
        {
          int number = __Pyx_BufFmt_ExpectNumber(&ts);
          if (number == -1) return NULL;
          ctx->new_count = (size_t)number;
        }
    }
  }
}
static CYTHON_INLINE void __Pyx_ZeroBuffer(Py_buffer* buf) {
  buf->buf = NULL;
  buf->obj = NULL;
  buf->strides = __Pyx_zeros;
  buf->shape = __Pyx_zeros;
  buf->suboffsets = __Pyx_minusones;
}
static CYTHON_INLINE int __Pyx_GetBufferAndValidate(
        Py_buffer* buf, PyObject* obj,  __Pyx_TypeInfo* dtype, int flags,
        int nd, int cast, __Pyx_BufFmt_StackElem* stack)
{
  if (obj == Py_None || obj == NULL) {
    __Pyx_ZeroBuffer(buf);
    return 0;
  }
  buf->buf = NULL;
  if (__Pyx_GetBuffer(obj, buf, flags) == -1) goto fail;
  if (buf->ndim != nd) {
    PyErr_Format(PyExc_ValueError,
                 "Buffer has wrong number of dimensions (expected %d, got %d)",
                 nd, buf->ndim);
    goto fail;
  }
  if (!cast) {
    __Pyx_BufFmt_Context ctx;
    __Pyx_BufFmt_Init(&ctx, stack, dtype);
    if (!__Pyx_BufFmt_CheckString(&ctx, buf->format)) goto fail;
  }
  if ((unsigned)buf->itemsize != dtype->size) {
    PyErr_Format(PyExc_ValueError,
      "Item size of buffer (%" CYTHON_FORMAT_SSIZE_T "d byte%s) does not match size of '%s' (%" CYTHON_FORMAT_SSIZE_T "d byte%s)",
      buf->itemsize, (buf->itemsize > 1) ? "s" : "",
      dtype->name, (Py_ssize_t)dtype->size, (dtype->size > 1) ? "s" : "");
    goto fail;
  }
  if (buf->suboffsets == NULL) buf->suboffsets = __Pyx_minusones;
  return 0;
fail:;
  __Pyx_ZeroBuffer(buf);
  return -1;
}
static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info) {
  if (info->buf == NULL) return;
  if (info->suboffsets == __Pyx_minusones) info->suboffsets = NULL;
  __Pyx_ReleaseBuffer(info);
}

static int
__Pyx_init_memviewslice(struct __pyx_memoryview_obj *memview,
                        int ndim,
                        __Pyx_memviewslice *memviewslice,
                        int memview_is_new_reference)
{
    __Pyx_RefNannyDeclarations
    int i, retval=-1;
    Py_buffer *buf = &memview->view;
    __Pyx_RefNannySetupContext("init_memviewslice", 0);
    if (!buf) {
        PyErr_SetString(PyExc_ValueError,
            "buf is NULL.");
        goto fail;
    } else if (memviewslice->memview || memviewslice->data) {
        PyErr_SetString(PyExc_ValueError,
            "memviewslice is already initialized!");
        goto fail;
    }
    if (buf->strides) {
        for (i = 0; i < ndim; i++) {
            memviewslice->strides[i] = buf->strides[i];
        }
    } else {
        Py_ssize_t stride = buf->itemsize;
        for (i = ndim - 1; i >= 0; i--) {
            memviewslice->strides[i] = stride;
            stride *= buf->shape[i];
        }
    }
    for (i = 0; i < ndim; i++) {
        memviewslice->shape[i]   = buf->shape[i];
        if (buf->suboffsets) {
            memviewslice->suboffsets[i] = buf->suboffsets[i];
        } else {
            memviewslice->suboffsets[i] = -1;
        }
    }
    memviewslice->memview = memview;
    memviewslice->data = (char *)buf->buf;
    if (__pyx_add_acquisition_count(memview) == 0 && !memview_is_new_reference) {
        Py_INCREF(memview);
    }
    retval = 0;
    goto no_fail;
fail:
    memviewslice->memview = 0;
    memviewslice->data = 0;
    retval = -1;
no_fail:
    __Pyx_RefNannyFinishContext();
    return retval;
}
static CYTHON_INLINE void __pyx_fatalerror(const char *fmt, ...) {
    va_list vargs;
    char msg[200];
    va_start(vargs, fmt);
#ifdef HAVE_STDARG_PROTOTYPES
    va_start(vargs, fmt);
#else
    va_start(vargs);
#endif
    vsnprintf(msg, 200, fmt, vargs);
    Py_FatalError(msg);
    va_end(vargs);
}
static CYTHON_INLINE int
__pyx_add_acquisition_count_locked(__pyx_atomic_int *acquisition_count,
                                   PyThread_type_lock lock)
{
    int result;
    PyThread_acquire_lock(lock, 1);
    result = (*acquisition_count)++;
    PyThread_release_lock(lock);
    return result;
}
static CYTHON_INLINE int
__pyx_sub_acquisition_count_locked(__pyx_atomic_int *acquisition_count,
                                   PyThread_type_lock lock)
{
    int result;
    PyThread_acquire_lock(lock, 1);
    result = (*acquisition_count)--;
    PyThread_release_lock(lock);
    return result;
}
static CYTHON_INLINE void
__Pyx_INC_MEMVIEW(__Pyx_memviewslice *memslice, int have_gil, int lineno)
{
    int first_time;
    struct __pyx_memoryview_obj *memview = memslice->memview;
    if (!memview || (PyObject *) memview == Py_None)
        return;
    if (__pyx_get_slice_count(memview) < 0)
        __pyx_fatalerror("Acquisition count is %d (line %d)",
                         __pyx_get_slice_count(memview), lineno);
    first_time = __pyx_add_acquisition_count(memview) == 0;
    if (first_time) {
        if (have_gil) {
            Py_INCREF((PyObject *) memview);
        } else {
            PyGILState_STATE _gilstate = PyGILState_Ensure();
            Py_INCREF((PyObject *) memview);
            PyGILState_Release(_gilstate);
        }
    }
}
static CYTHON_INLINE void __Pyx_XDEC_MEMVIEW(__Pyx_memviewslice *memslice,
                                             int have_gil, int lineno) {
    int last_time;
    struct __pyx_memoryview_obj *memview = memslice->memview;
    if (!memview ) {
        return;
    } else if ((PyObject *) memview == Py_None) {
        memslice->memview = NULL;
        return;
    }
    if (__pyx_get_slice_count(memview) <= 0)
        __pyx_fatalerror("Acquisition count is %d (line %d)",
                         __pyx_get_slice_count(memview), lineno);
    last_time = __pyx_sub_acquisition_count(memview) == 1;
    memslice->data = NULL;
    if (last_time) {
        if (have_gil) {
            Py_CLEAR(memslice->memview);
        } else {
            PyGILState_STATE _gilstate = PyGILState_Ensure();
            Py_CLEAR(memslice->memview);
            PyGILState_Release(_gilstate);
        }
    } else {
        memslice->memview = NULL;
    }
}

static CYTHON_INLINE PyObject *__Pyx_GetModuleGlobalName(PyObject *name) {
    PyObject *result;
#if CYTHON_COMPILING_IN_CPYTHON
    result = PyDict_GetItem(__pyx_d, name);
    if (likely(result)) {
        Py_INCREF(result);
    } else {
#else
    result = PyObject_GetItem(__pyx_d, name);
    if (!result) {
        PyErr_Clear();
#endif
        result = __Pyx_GetBuiltinName(name);
    }
    return result;
}

#if CYTHON_COMPILING_IN_CPYTHON
static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg) {
    PyObject *self, *result;
    PyCFunction cfunc;
    cfunc = PyCFunction_GET_FUNCTION(func);
    self = PyCFunction_GET_SELF(func);
    if (unlikely(Py_EnterRecursiveCall((char*)" while calling a Python object")))
        return NULL;
    result = cfunc(self, arg);
    Py_LeaveRecursiveCall();
    if (unlikely(!result) && unlikely(!PyErr_Occurred())) {
        PyErr_SetString(
            PyExc_SystemError,
            "NULL result without error in PyObject_Call");
    }
    return result;
}
#endif

#if CYTHON_COMPILING_IN_CPYTHON
static PyObject* __Pyx__PyObject_CallOneArg(PyObject *func, PyObject *arg) {
    PyObject *result;
    PyObject *args = PyTuple_New(1);
    if (unlikely(!args)) return NULL;
    Py_INCREF(arg);
    PyTuple_SET_ITEM(args, 0, arg);
    result = __Pyx_PyObject_Call(func, args, NULL);
    Py_DECREF(args);
    return result;
}
static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) {
#ifdef __Pyx_CyFunction_USED
    if (likely(PyCFunction_Check(func) || PyObject_TypeCheck(func, __pyx_CyFunctionType))) {
#else
    if (likely(PyCFunction_Check(func))) {
#endif
        if (likely(PyCFunction_GET_FLAGS(func) & METH_O)) {
            return __Pyx_PyObject_CallMethO(func, arg);
        }
    }
    return __Pyx__PyObject_CallOneArg(func, arg);
}
#else
static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) {
    PyObject* args = PyTuple_Pack(1, arg);
    return (likely(args)) ? __Pyx_PyObject_Call(func, args, NULL) : NULL;
}
#endif

static PyObject* __Pyx_ImportFrom(PyObject* module, PyObject* name) {
    PyObject* value = __Pyx_PyObject_GetAttrStr(module, name);
    if (unlikely(!value) && PyErr_ExceptionMatches(PyExc_AttributeError)) {
        PyErr_Format(PyExc_ImportError,
        #if PY_MAJOR_VERSION < 3
            "cannot import name %.230s", PyString_AS_STRING(name));
        #else
            "cannot import name %S", name);
        #endif
    }
    return value;
}

static CYTHON_INLINE void __Pyx_ExceptionSave(PyObject **type, PyObject **value, PyObject **tb) {
#if CYTHON_COMPILING_IN_CPYTHON
    PyThreadState *tstate = PyThreadState_GET();
    *type = tstate->exc_type;
    *value = tstate->exc_value;
    *tb = tstate->exc_traceback;
    Py_XINCREF(*type);
    Py_XINCREF(*value);
    Py_XINCREF(*tb);
#else
    PyErr_GetExcInfo(type, value, tb);
#endif
}
static void __Pyx_ExceptionReset(PyObject *type, PyObject *value, PyObject *tb) {
#if CYTHON_COMPILING_IN_CPYTHON
    PyObject *tmp_type, *tmp_value, *tmp_tb;
    PyThreadState *tstate = PyThreadState_GET();
    tmp_type = tstate->exc_type;
    tmp_value = tstate->exc_value;
    tmp_tb = tstate->exc_traceback;
    tstate->exc_type = type;
    tstate->exc_value = value;
    tstate->exc_traceback = tb;
    Py_XDECREF(tmp_type);
    Py_XDECREF(tmp_value);
    Py_XDECREF(tmp_tb);
#else
    PyErr_SetExcInfo(type, value, tb);
#endif
}

static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb) {
    PyObject *local_type, *local_value, *local_tb;
#if CYTHON_COMPILING_IN_CPYTHON
    PyObject *tmp_type, *tmp_value, *tmp_tb;
    PyThreadState *tstate = PyThreadState_GET();
    local_type = tstate->curexc_type;
    local_value = tstate->curexc_value;
    local_tb = tstate->curexc_traceback;
    tstate->curexc_type = 0;
    tstate->curexc_value = 0;
    tstate->curexc_traceback = 0;
#else
    PyErr_Fetch(&local_type, &local_value, &local_tb);
#endif
    PyErr_NormalizeException(&local_type, &local_value, &local_tb);
#if CYTHON_COMPILING_IN_CPYTHON
    if (unlikely(tstate->curexc_type))
#else
    if (unlikely(PyErr_Occurred()))
#endif
        goto bad;
    #if PY_MAJOR_VERSION >= 3
    if (local_tb) {
        if (unlikely(PyException_SetTraceback(local_value, local_tb) < 0))
            goto bad;
    }
    #endif
    Py_XINCREF(local_tb);
    Py_XINCREF(local_type);
    Py_XINCREF(local_value);
    *type = local_type;
    *value = local_value;
    *tb = local_tb;
#if CYTHON_COMPILING_IN_CPYTHON
    tmp_type = tstate->exc_type;
    tmp_value = tstate->exc_value;
    tmp_tb = tstate->exc_traceback;
    tstate->exc_type = local_type;
    tstate->exc_value = local_value;
    tstate->exc_traceback = local_tb;
    Py_XDECREF(tmp_type);
    Py_XDECREF(tmp_value);
    Py_XDECREF(tmp_tb);
#else
    PyErr_SetExcInfo(local_type, local_value, local_tb);
#endif
    return 0;
bad:
    *type = 0;
    *value = 0;
    *tb = 0;
    Py_XDECREF(local_type);
    Py_XDECREF(local_value);
    Py_XDECREF(local_tb);
    return -1;
}

static void __Pyx_RaiseArgumentTypeInvalid(const char* name, PyObject *obj, PyTypeObject *type) {
    PyErr_Format(PyExc_TypeError,
        "Argument '%.200s' has incorrect type (expected %.200s, got %.200s)",
        name, type->tp_name, Py_TYPE(obj)->tp_name);
}
static CYTHON_INLINE int __Pyx_ArgTypeTest(PyObject *obj, PyTypeObject *type, int none_allowed,
    const char *name, int exact)
{
    if (unlikely(!type)) {
        PyErr_SetString(PyExc_SystemError, "Missing type object");
        return 0;
    }
    if (none_allowed && obj == Py_None) return 1;
    else if (exact) {
        if (likely(Py_TYPE(obj) == type)) return 1;
        #if PY_MAJOR_VERSION == 2
        else if ((type == &PyBaseString_Type) && likely(__Pyx_PyBaseString_CheckExact(obj))) return 1;
        #endif
    }
    else {
        if (likely(PyObject_TypeCheck(obj, type))) return 1;
    }
    __Pyx_RaiseArgumentTypeInvalid(name, obj, type);
    return 0;
}

static CYTHON_INLINE int __Pyx_CheckKeywordStrings(
    PyObject *kwdict,
    const char* function_name,
    int kw_allowed)
{
    PyObject* key = 0;
    Py_ssize_t pos = 0;
#if CYTHON_COMPILING_IN_PYPY
    if (!kw_allowed && PyDict_Next(kwdict, &pos, &key, 0))
        goto invalid_keyword;
    return 1;
#else
    while (PyDict_Next(kwdict, &pos, &key, 0)) {
        #if PY_MAJOR_VERSION < 3
        if (unlikely(!PyString_CheckExact(key)) && unlikely(!PyString_Check(key)))
        #endif
            if (unlikely(!PyUnicode_Check(key)))
                goto invalid_keyword_type;
    }
    if ((!kw_allowed) && unlikely(key))
        goto invalid_keyword;
    return 1;
invalid_keyword_type:
    PyErr_Format(PyExc_TypeError,
        "%.200s() keywords must be strings", function_name);
    return 0;
#endif
invalid_keyword:
    PyErr_Format(PyExc_TypeError,
    #if PY_MAJOR_VERSION < 3
        "%.200s() got an unexpected keyword argument '%.200s'",
        function_name, PyString_AsString(key));
    #else
        "%s() got an unexpected keyword argument '%U'",
        function_name, key);
    #endif
    return 0;
}

static CYTHON_INLINE PyObject *__Pyx_PyIter_Next2(PyObject* iterator, PyObject* defval) {
    PyObject* next;
    iternextfunc iternext = Py_TYPE(iterator)->tp_iternext;
#if CYTHON_COMPILING_IN_CPYTHON
    if (unlikely(!iternext)) {
#else
    if (unlikely(!iternext) || unlikely(!PyIter_Check(iterator))) {
#endif
        PyErr_Format(PyExc_TypeError,
            "%.200s object is not an iterator", Py_TYPE(iterator)->tp_name);
        return NULL;
    }
    next = iternext(iterator);
    if (likely(next))
        return next;
#if CYTHON_COMPILING_IN_CPYTHON
#if PY_VERSION_HEX >= 0x02070000
    if (unlikely(iternext == &_PyObject_NextNotImplemented))
        return NULL;
#endif
#endif
    if (defval) {
        PyObject* exc_type = PyErr_Occurred();
        if (exc_type) {
            if (unlikely(exc_type != PyExc_StopIteration) &&
                    !PyErr_GivenExceptionMatches(exc_type, PyExc_StopIteration))
                return NULL;
            PyErr_Clear();
        }
        Py_INCREF(defval);
        return defval;
    }
    if (!PyErr_Occurred())
        PyErr_SetNone(PyExc_StopIteration);
    return NULL;
}

#if CYTHON_COMPILING_IN_CPYTHON
static CYTHON_INLINE PyObject* __Pyx_PyObject_CallNoArg(PyObject *func) {
#ifdef __Pyx_CyFunction_USED
    if (likely(PyCFunction_Check(func) || PyObject_TypeCheck(func, __pyx_CyFunctionType))) {
#else
    if (likely(PyCFunction_Check(func))) {
#endif
        if (likely(PyCFunction_GET_FLAGS(func) & METH_NOARGS)) {
            return __Pyx_PyObject_CallMethO(func, NULL);
        }
    }
    return __Pyx_PyObject_Call(func, __pyx_empty_tuple, NULL);
}
#endif

static void __Pyx_WriteUnraisable(const char *name, CYTHON_UNUSED int clineno,
                                  CYTHON_UNUSED int lineno, CYTHON_UNUSED const char *filename,
                                  int full_traceback) {
    PyObject *old_exc, *old_val, *old_tb;
    PyObject *ctx;
    __Pyx_ErrFetch(&old_exc, &old_val, &old_tb);
    if (full_traceback) {
        Py_XINCREF(old_exc);
        Py_XINCREF(old_val);
        Py_XINCREF(old_tb);
        __Pyx_ErrRestore(old_exc, old_val, old_tb);
        PyErr_PrintEx(1);
    }
    #if PY_MAJOR_VERSION < 3
    ctx = PyString_FromString(name);
    #else
    ctx = PyUnicode_FromString(name);
    #endif
    __Pyx_ErrRestore(old_exc, old_val, old_tb);
    if (!ctx) {
        PyErr_WriteUnraisable(Py_None);
    } else {
        PyErr_WriteUnraisable(ctx);
        Py_DECREF(ctx);
    }
}

static CYTHON_INLINE long __Pyx_mod_long(long a, long b) {
    long r = a % b;
    r += ((r != 0) & ((r ^ b) < 0)) * b;
    return r;
}

static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname) {
    PyErr_Format(PyExc_UnboundLocalError, "local variable '%s' referenced before assignment", varname);
}

static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected) {
    PyErr_Format(PyExc_ValueError,
                 "too many values to unpack (expected %" CYTHON_FORMAT_SSIZE_T "d)", expected);
}

static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index) {
    PyErr_Format(PyExc_ValueError,
                 "need more than %" CYTHON_FORMAT_SSIZE_T "d value%.1s to unpack",
                 index, (index == 1) ? "" : "s");
}

static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void) {
    PyErr_SetString(PyExc_TypeError, "'NoneType' object is not iterable");
}

static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type) {
    if (unlikely(!type)) {
        PyErr_SetString(PyExc_SystemError, "Missing type object");
        return 0;
    }
    if (likely(PyObject_TypeCheck(obj, type)))
        return 1;
    PyErr_Format(PyExc_TypeError, "Cannot convert %.200s to %.200s",
                 Py_TYPE(obj)->tp_name, type->tp_name);
    return 0;
}

static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals) {
#if CYTHON_COMPILING_IN_PYPY
    return PyObject_RichCompareBool(s1, s2, equals);
#else
    if (s1 == s2) {
        return (equals == Py_EQ);
    } else if (PyBytes_CheckExact(s1) & PyBytes_CheckExact(s2)) {
        const char *ps1, *ps2;
        Py_ssize_t length = PyBytes_GET_SIZE(s1);
        if (length != PyBytes_GET_SIZE(s2))
            return (equals == Py_NE);
        ps1 = PyBytes_AS_STRING(s1);
        ps2 = PyBytes_AS_STRING(s2);
        if (ps1[0] != ps2[0]) {
            return (equals == Py_NE);
        } else if (length == 1) {
            return (equals == Py_EQ);
        } else {
            int result = memcmp(ps1, ps2, (size_t)length);
            return (equals == Py_EQ) ? (result == 0) : (result != 0);
        }
    } else if ((s1 == Py_None) & PyBytes_CheckExact(s2)) {
        return (equals == Py_NE);
    } else if ((s2 == Py_None) & PyBytes_CheckExact(s1)) {
        return (equals == Py_NE);
    } else {
        int result;
        PyObject* py_result = PyObject_RichCompare(s1, s2, equals);
        if (!py_result)
            return -1;
        result = __Pyx_PyObject_IsTrue(py_result);
        Py_DECREF(py_result);
        return result;
    }
#endif
}

static CYTHON_INLINE int __Pyx_PyUnicode_Equals(PyObject* s1, PyObject* s2, int equals) {
#if CYTHON_COMPILING_IN_PYPY
    return PyObject_RichCompareBool(s1, s2, equals);
#else
#if PY_MAJOR_VERSION < 3
    PyObject* owned_ref = NULL;
#endif
    int s1_is_unicode, s2_is_unicode;
    if (s1 == s2) {
        goto return_eq;
    }
    s1_is_unicode = PyUnicode_CheckExact(s1);
    s2_is_unicode = PyUnicode_CheckExact(s2);
#if PY_MAJOR_VERSION < 3
    if ((s1_is_unicode & (!s2_is_unicode)) && PyString_CheckExact(s2)) {
        owned_ref = PyUnicode_FromObject(s2);
        if (unlikely(!owned_ref))
            return -1;
        s2 = owned_ref;
        s2_is_unicode = 1;
    } else if ((s2_is_unicode & (!s1_is_unicode)) && PyString_CheckExact(s1)) {
        owned_ref = PyUnicode_FromObject(s1);
        if (unlikely(!owned_ref))
            return -1;
        s1 = owned_ref;
        s1_is_unicode = 1;
    } else if (((!s2_is_unicode) & (!s1_is_unicode))) {
        return __Pyx_PyBytes_Equals(s1, s2, equals);
    }
#endif
    if (s1_is_unicode & s2_is_unicode) {
        Py_ssize_t length;
        int kind;
        void *data1, *data2;
        if (unlikely(__Pyx_PyUnicode_READY(s1) < 0) || unlikely(__Pyx_PyUnicode_READY(s2) < 0))
            return -1;
        length = __Pyx_PyUnicode_GET_LENGTH(s1);
        if (length != __Pyx_PyUnicode_GET_LENGTH(s2)) {
            goto return_ne;
        }
        kind = __Pyx_PyUnicode_KIND(s1);
        if (kind != __Pyx_PyUnicode_KIND(s2)) {
            goto return_ne;
        }
        data1 = __Pyx_PyUnicode_DATA(s1);
        data2 = __Pyx_PyUnicode_DATA(s2);
        if (__Pyx_PyUnicode_READ(kind, data1, 0) != __Pyx_PyUnicode_READ(kind, data2, 0)) {
            goto return_ne;
        } else if (length == 1) {
            goto return_eq;
        } else {
            int result = memcmp(data1, data2, (size_t)(length * kind));
            #if PY_MAJOR_VERSION < 3
            Py_XDECREF(owned_ref);
            #endif
            return (equals == Py_EQ) ? (result == 0) : (result != 0);
        }
    } else if ((s1 == Py_None) & s2_is_unicode) {
        goto return_ne;
    } else if ((s2 == Py_None) & s1_is_unicode) {
        goto return_ne;
    } else {
        int result;
        PyObject* py_result = PyObject_RichCompare(s1, s2, equals);
        if (!py_result)
            return -1;
        result = __Pyx_PyObject_IsTrue(py_result);
        Py_DECREF(py_result);
        return result;
    }
return_eq:
    #if PY_MAJOR_VERSION < 3
    Py_XDECREF(owned_ref);
    #endif
    return (equals == Py_EQ);
return_ne:
    #if PY_MAJOR_VERSION < 3
    Py_XDECREF(owned_ref);
    #endif
    return (equals == Py_NE);
#endif
}

static CYTHON_INLINE Py_ssize_t __Pyx_div_Py_ssize_t(Py_ssize_t a, Py_ssize_t b) {
    Py_ssize_t q = a / b;
    Py_ssize_t r = a - q*b;
    q -= ((r != 0) & ((r ^ b) < 0));
    return q;
}

static CYTHON_INLINE PyObject *__Pyx_GetAttr(PyObject *o, PyObject *n) {
#if CYTHON_COMPILING_IN_CPYTHON
#if PY_MAJOR_VERSION >= 3
    if (likely(PyUnicode_Check(n)))
#else
    if (likely(PyString_Check(n)))
#endif
        return __Pyx_PyObject_GetAttrStr(o, n);
#endif
    return PyObject_GetAttr(o, n);
}

static CYTHON_INLINE PyObject* __Pyx_decode_c_string(
         const char* cstring, Py_ssize_t start, Py_ssize_t stop,
         const char* encoding, const char* errors,
         PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors)) {
    Py_ssize_t length;
    if (unlikely((start < 0) | (stop < 0))) {
        length = strlen(cstring);
        if (start < 0) {
            start += length;
            if (start < 0)
                start = 0;
        }
        if (stop < 0)
            stop += length;
    }
    length = stop - start;
    if (unlikely(length <= 0))
        return PyUnicode_FromUnicode(NULL, 0);
    cstring += start;
    if (decode_func) {
        return decode_func(cstring, length, errors);
    } else {
        return PyUnicode_Decode(cstring, length, encoding, errors);
    }
}

static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb) {
    PyObject *tmp_type, *tmp_value, *tmp_tb;
#if CYTHON_COMPILING_IN_CPYTHON
    PyThreadState *tstate = PyThreadState_GET();
    tmp_type = tstate->exc_type;
    tmp_value = tstate->exc_value;
    tmp_tb = tstate->exc_traceback;
    tstate->exc_type = *type;
    tstate->exc_value = *value;
    tstate->exc_traceback = *tb;
#else
    PyErr_GetExcInfo(&tmp_type, &tmp_value, &tmp_tb);
    PyErr_SetExcInfo(*type, *value, *tb);
#endif
    *type = tmp_type;
    *value = tmp_value;
    *tb = tmp_tb;
}

static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j) {
    PyObject *r;
    if (!j) return NULL;
    r = PyObject_GetItem(o, j);
    Py_DECREF(j);
    return r;
}
static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i,
                                                              int wraparound, int boundscheck) {
#if CYTHON_COMPILING_IN_CPYTHON
    if (wraparound & unlikely(i < 0)) i += PyList_GET_SIZE(o);
    if ((!boundscheck) || likely((0 <= i) & (i < PyList_GET_SIZE(o)))) {
        PyObject *r = PyList_GET_ITEM(o, i);
        Py_INCREF(r);
        return r;
    }
    return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i));
#else
    return PySequence_GetItem(o, i);
#endif
}
static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i,
                                                              int wraparound, int boundscheck) {
#if CYTHON_COMPILING_IN_CPYTHON
    if (wraparound & unlikely(i < 0)) i += PyTuple_GET_SIZE(o);
    if ((!boundscheck) || likely((0 <= i) & (i < PyTuple_GET_SIZE(o)))) {
        PyObject *r = PyTuple_GET_ITEM(o, i);
        Py_INCREF(r);
        return r;
    }
    return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i));
#else
    return PySequence_GetItem(o, i);
#endif
}
static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i,
                                                     int is_list, int wraparound, int boundscheck) {
#if CYTHON_COMPILING_IN_CPYTHON
    if (is_list || PyList_CheckExact(o)) {
        Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyList_GET_SIZE(o);
        if ((!boundscheck) || (likely((n >= 0) & (n < PyList_GET_SIZE(o))))) {
            PyObject *r = PyList_GET_ITEM(o, n);
            Py_INCREF(r);
            return r;
        }
    }
    else if (PyTuple_CheckExact(o)) {
        Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyTuple_GET_SIZE(o);
        if ((!boundscheck) || likely((n >= 0) & (n < PyTuple_GET_SIZE(o)))) {
            PyObject *r = PyTuple_GET_ITEM(o, n);
            Py_INCREF(r);
            return r;
        }
    } else {
        PySequenceMethods *m = Py_TYPE(o)->tp_as_sequence;
        if (likely(m && m->sq_item)) {
            if (wraparound && unlikely(i < 0) && likely(m->sq_length)) {
                Py_ssize_t l = m->sq_length(o);
                if (likely(l >= 0)) {
                    i += l;
                } else {
                    if (PyErr_ExceptionMatches(PyExc_OverflowError))
                        PyErr_Clear();
                    else
                        return NULL;
                }
            }
            return m->sq_item(o, i);
        }
    }
#else
    if (is_list || PySequence_Check(o)) {
        return PySequence_GetItem(o, i);
    }
#endif
    return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i));
}

static CYTHON_INLINE long __Pyx_div_long(long a, long b) {
    long q = a / b;
    long r = a - q*b;
    q -= ((r != 0) & ((r ^ b) < 0));
    return q;
}

static int __Pyx_SetVtable(PyObject *dict, void *vtable) {
#if PY_VERSION_HEX >= 0x02070000
    PyObject *ob = PyCapsule_New(vtable, 0, 0);
#else
    PyObject *ob = PyCObject_FromVoidPtr(vtable, 0);
#endif
    if (!ob)
        goto bad;
    if (PyDict_SetItem(dict, __pyx_n_s_pyx_vtable, ob) < 0)
        goto bad;
    Py_DECREF(ob);
    return 0;
bad:
    Py_XDECREF(ob);
    return -1;
}

static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line) {
    int start = 0, mid = 0, end = count - 1;
    if (end >= 0 && code_line > entries[end].code_line) {
        return count;
    }
    while (start < end) {
        mid = (start + end) / 2;
        if (code_line < entries[mid].code_line) {
            end = mid;
        } else if (code_line > entries[mid].code_line) {
             start = mid + 1;
        } else {
            return mid;
        }
    }
    if (code_line <= entries[mid].code_line) {
        return mid;
    } else {
        return mid + 1;
    }
}
static PyCodeObject *__pyx_find_code_object(int code_line) {
    PyCodeObject* code_object;
    int pos;
    if (unlikely(!code_line) || unlikely(!__pyx_code_cache.entries)) {
        return NULL;
    }
    pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line);
    if (unlikely(pos >= __pyx_code_cache.count) || unlikely(__pyx_code_cache.entries[pos].code_line != code_line)) {
        return NULL;
    }
    code_object = __pyx_code_cache.entries[pos].code_object;
    Py_INCREF(code_object);
    return code_object;
}
static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object) {
    int pos, i;
    __Pyx_CodeObjectCacheEntry* entries = __pyx_code_cache.entries;
    if (unlikely(!code_line)) {
        return;
    }
    if (unlikely(!entries)) {
        entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Malloc(64*sizeof(__Pyx_CodeObjectCacheEntry));
        if (likely(entries)) {
            __pyx_code_cache.entries = entries;
            __pyx_code_cache.max_count = 64;
            __pyx_code_cache.count = 1;
            entries[0].code_line = code_line;
            entries[0].code_object = code_object;
            Py_INCREF(code_object);
        }
        return;
    }
    pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line);
    if ((pos < __pyx_code_cache.count) && unlikely(__pyx_code_cache.entries[pos].code_line == code_line)) {
        PyCodeObject* tmp = entries[pos].code_object;
        entries[pos].code_object = code_object;
        Py_DECREF(tmp);
        return;
    }
    if (__pyx_code_cache.count == __pyx_code_cache.max_count) {
        int new_max = __pyx_code_cache.max_count + 64;
        entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Realloc(
            __pyx_code_cache.entries, (size_t)new_max*sizeof(__Pyx_CodeObjectCacheEntry));
        if (unlikely(!entries)) {
            return;
        }
        __pyx_code_cache.entries = entries;
        __pyx_code_cache.max_count = new_max;
    }
    for (i=__pyx_code_cache.count; i>pos; i--) {
        entries[i] = entries[i-1];
    }
    entries[pos].code_line = code_line;
    entries[pos].code_object = code_object;
    __pyx_code_cache.count++;
    Py_INCREF(code_object);
}

#include "compile.h"
#include "frameobject.h"
#include "traceback.h"
static PyCodeObject* __Pyx_CreateCodeObjectForTraceback(
            const char *funcname, int c_line,
            int py_line, const char *filename) {
    PyCodeObject *py_code = 0;
    PyObject *py_srcfile = 0;
    PyObject *py_funcname = 0;
    #if PY_MAJOR_VERSION < 3
    py_srcfile = PyString_FromString(filename);
    #else
    py_srcfile = PyUnicode_FromString(filename);
    #endif
    if (!py_srcfile) goto bad;
    if (c_line) {
        #if PY_MAJOR_VERSION < 3
        py_funcname = PyString_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line);
        #else
        py_funcname = PyUnicode_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line);
        #endif
    }
    else {
        #if PY_MAJOR_VERSION < 3
        py_funcname = PyString_FromString(funcname);
        #else
        py_funcname = PyUnicode_FromString(funcname);
        #endif
    }
    if (!py_funcname) goto bad;
    py_code = __Pyx_PyCode_New(
        0,
        0,
        0,
        0,
        0,
        __pyx_empty_bytes, /*PyObject *code,*/
        __pyx_empty_tuple, /*PyObject *consts,*/
        __pyx_empty_tuple, /*PyObject *names,*/
        __pyx_empty_tuple, /*PyObject *varnames,*/
        __pyx_empty_tuple, /*PyObject *freevars,*/
        __pyx_empty_tuple, /*PyObject *cellvars,*/
        py_srcfile,   /*PyObject *filename,*/
        py_funcname,  /*PyObject *name,*/
        py_line,
        __pyx_empty_bytes  /*PyObject *lnotab*/
    );
    Py_DECREF(py_srcfile);
    Py_DECREF(py_funcname);
    return py_code;
bad:
    Py_XDECREF(py_srcfile);
    Py_XDECREF(py_funcname);
    return NULL;
}
static void __Pyx_AddTraceback(const char *funcname, int c_line,
                               int py_line, const char *filename) {
    PyCodeObject *py_code = 0;
    PyFrameObject *py_frame = 0;
    py_code = __pyx_find_code_object(c_line ? c_line : py_line);
    if (!py_code) {
        py_code = __Pyx_CreateCodeObjectForTraceback(
            funcname, c_line, py_line, filename);
        if (!py_code) goto bad;
        __pyx_insert_code_object(c_line ? c_line : py_line, py_code);
    }
    py_frame = PyFrame_New(
        PyThreadState_GET(), /*PyThreadState *tstate,*/
        py_code,             /*PyCodeObject *code,*/
        __pyx_d,      /*PyObject *globals,*/
        0                    /*PyObject *locals*/
    );
    if (!py_frame) goto bad;
    py_frame->f_lineno = py_line;
    PyTraceBack_Here(py_frame);
bad:
    Py_XDECREF(py_code);
    Py_XDECREF(py_frame);
}

#if PY_MAJOR_VERSION < 3
static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags) {
    if (PyObject_CheckBuffer(obj)) return PyObject_GetBuffer(obj, view, flags);
        if (PyObject_TypeCheck(obj, __pyx_ptype_5numpy_ndarray)) return __pyx_pw_5numpy_7ndarray_1__getbuffer__(obj, view, flags);
        if (PyObject_TypeCheck(obj, __pyx_array_type)) return __pyx_array_getbuffer(obj, view, flags);
        if (PyObject_TypeCheck(obj, __pyx_memoryview_type)) return __pyx_memoryview_getbuffer(obj, view, flags);
    PyErr_Format(PyExc_TypeError, "'%.200s' does not have the buffer interface", Py_TYPE(obj)->tp_name);
    return -1;
}
static void __Pyx_ReleaseBuffer(Py_buffer *view) {
    PyObject *obj = view->obj;
    if (!obj) return;
    if (PyObject_CheckBuffer(obj)) {
        PyBuffer_Release(view);
        return;
    }
        if (PyObject_TypeCheck(obj, __pyx_ptype_5numpy_ndarray)) { __pyx_pw_5numpy_7ndarray_3__releasebuffer__(obj, view); return; }
    Py_DECREF(obj);
    view->obj = NULL;
}
#endif


            static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level) {
    PyObject *empty_list = 0;
    PyObject *module = 0;
    PyObject *global_dict = 0;
    PyObject *empty_dict = 0;
    PyObject *list;
    #if PY_VERSION_HEX < 0x03030000
    PyObject *py_import;
    py_import = __Pyx_PyObject_GetAttrStr(__pyx_b, __pyx_n_s_import);
    if (!py_import)
        goto bad;
    #endif
    if (from_list)
        list = from_list;
    else {
        empty_list = PyList_New(0);
        if (!empty_list)
            goto bad;
        list = empty_list;
    }
    global_dict = PyModule_GetDict(__pyx_m);
    if (!global_dict)
        goto bad;
    empty_dict = PyDict_New();
    if (!empty_dict)
        goto bad;
    {
        #if PY_MAJOR_VERSION >= 3
        if (level == -1) {
            if (strchr(__Pyx_MODULE_NAME, '.')) {
                #if PY_VERSION_HEX < 0x03030000
                PyObject *py_level = PyInt_FromLong(1);
                if (!py_level)
                    goto bad;
                module = PyObject_CallFunctionObjArgs(py_import,
                    name, global_dict, empty_dict, list, py_level, NULL);
                Py_DECREF(py_level);
                #else
                module = PyImport_ImportModuleLevelObject(
                    name, global_dict, empty_dict, list, 1);
                #endif
                if (!module) {
                    if (!PyErr_ExceptionMatches(PyExc_ImportError))
                        goto bad;
                    PyErr_Clear();
                }
            }
            level = 0;
        }
        #endif
        if (!module) {
            #if PY_VERSION_HEX < 0x03030000
            PyObject *py_level = PyInt_FromLong(level);
            if (!py_level)
                goto bad;
            module = PyObject_CallFunctionObjArgs(py_import,
                name, global_dict, empty_dict, list, py_level, NULL);
            Py_DECREF(py_level);
            #else
            module = PyImport_ImportModuleLevelObject(
                name, global_dict, empty_dict, list, level);
            #endif
        }
    }
bad:
    #if PY_VERSION_HEX < 0x03030000
    Py_XDECREF(py_import);
    #endif
    Py_XDECREF(empty_list);
    Py_XDECREF(empty_dict);
    return module;
}

static int
__pyx_typeinfo_cmp(__Pyx_TypeInfo *a, __Pyx_TypeInfo *b)
{
    int i;
    if (!a || !b)
        return 0;
    if (a == b)
        return 1;
    if (a->size != b->size || a->typegroup != b->typegroup ||
            a->is_unsigned != b->is_unsigned || a->ndim != b->ndim) {
        if (a->typegroup == 'H' || b->typegroup == 'H') {
            return a->size == b->size;
        } else {
            return 0;
        }
    }
    if (a->ndim) {
        for (i = 0; i < a->ndim; i++)
            if (a->arraysize[i] != b->arraysize[i])
                return 0;
    }
    if (a->typegroup == 'S') {
        if (a->flags != b->flags)
            return 0;
        if (a->fields || b->fields) {
            if (!(a->fields && b->fields))
                return 0;
            for (i = 0; a->fields[i].type && b->fields[i].type; i++) {
                __Pyx_StructField *field_a = a->fields + i;
                __Pyx_StructField *field_b = b->fields + i;
                if (field_a->offset != field_b->offset ||
                    !__pyx_typeinfo_cmp(field_a->type, field_b->type))
                    return 0;
            }
            return !a->fields[i].type && !b->fields[i].type;
        }
    }
    return 1;
}

static int
__pyx_check_strides(Py_buffer *buf, int dim, int ndim, int spec)
{
    if (buf->shape[dim] <= 1)
        return 1;
    if (buf->strides) {
        if (spec & __Pyx_MEMVIEW_CONTIG) {
            if (spec & (__Pyx_MEMVIEW_PTR|__Pyx_MEMVIEW_FULL)) {
                if (buf->strides[dim] != sizeof(void *)) {
                    PyErr_Format(PyExc_ValueError,
                                 "Buffer is not indirectly contiguous "
                                 "in dimension %d.", dim);
                    goto fail;
                }
            } else if (buf->strides[dim] != buf->itemsize) {
                PyErr_SetString(PyExc_ValueError,
                                "Buffer and memoryview are not contiguous "
                                "in the same dimension.");
                goto fail;
            }
        }
        if (spec & __Pyx_MEMVIEW_FOLLOW) {
            Py_ssize_t stride = buf->strides[dim];
            if (stride < 0)
                stride = -stride;
            if (stride < buf->itemsize) {
                PyErr_SetString(PyExc_ValueError,
                                "Buffer and memoryview are not contiguous "
                                "in the same dimension.");
                goto fail;
            }
        }
    } else {
        if (spec & __Pyx_MEMVIEW_CONTIG && dim != ndim - 1) {
            PyErr_Format(PyExc_ValueError,
                         "C-contiguous buffer is not contiguous in "
                         "dimension %d", dim);
            goto fail;
        } else if (spec & (__Pyx_MEMVIEW_PTR)) {
            PyErr_Format(PyExc_ValueError,
                         "C-contiguous buffer is not indirect in "
                         "dimension %d", dim);
            goto fail;
        } else if (buf->suboffsets) {
            PyErr_SetString(PyExc_ValueError,
                            "Buffer exposes suboffsets but no strides");
            goto fail;
        }
    }
    return 1;
fail:
    return 0;
}
static int
__pyx_check_suboffsets(Py_buffer *buf, int dim, CYTHON_UNUSED int ndim, int spec)
{
    if (spec & __Pyx_MEMVIEW_DIRECT) {
        if (buf->suboffsets && buf->suboffsets[dim] >= 0) {
            PyErr_Format(PyExc_ValueError,
                         "Buffer not compatible with direct access "
                         "in dimension %d.", dim);
            goto fail;
        }
    }
    if (spec & __Pyx_MEMVIEW_PTR) {
        if (!buf->suboffsets || (buf->suboffsets && buf->suboffsets[dim] < 0)) {
            PyErr_Format(PyExc_ValueError,
                         "Buffer is not indirectly accessible "
                         "in dimension %d.", dim);
            goto fail;
        }
    }
    return 1;
fail:
    return 0;
}
static int
__pyx_verify_contig(Py_buffer *buf, int ndim, int c_or_f_flag)
{
    int i;
    if (c_or_f_flag & __Pyx_IS_F_CONTIG) {
        Py_ssize_t stride = 1;
        for (i = 0; i < ndim; i++) {
            if (stride * buf->itemsize != buf->strides[i] &&
                    buf->shape[i] > 1)
            {
                PyErr_SetString(PyExc_ValueError,
                    "Buffer not fortran contiguous.");
                goto fail;
            }
            stride = stride * buf->shape[i];
        }
    } else if (c_or_f_flag & __Pyx_IS_C_CONTIG) {
        Py_ssize_t stride = 1;
        for (i = ndim - 1; i >- 1; i--) {
            if (stride * buf->itemsize != buf->strides[i] &&
                    buf->shape[i] > 1) {
                PyErr_SetString(PyExc_ValueError,
                    "Buffer not C contiguous.");
                goto fail;
            }
            stride = stride * buf->shape[i];
        }
    }
    return 1;
fail:
    return 0;
}
static int __Pyx_ValidateAndInit_memviewslice(
                int *axes_specs,
                int c_or_f_flag,
                int buf_flags,
                int ndim,
                __Pyx_TypeInfo *dtype,
                __Pyx_BufFmt_StackElem stack[],
                __Pyx_memviewslice *memviewslice,
                PyObject *original_obj)
{
    struct __pyx_memoryview_obj *memview, *new_memview;
    __Pyx_RefNannyDeclarations
    Py_buffer *buf;
    int i, spec = 0, retval = -1;
    __Pyx_BufFmt_Context ctx;
    int from_memoryview = __pyx_memoryview_check(original_obj);
    __Pyx_RefNannySetupContext("ValidateAndInit_memviewslice", 0);
    if (from_memoryview && __pyx_typeinfo_cmp(dtype, ((struct __pyx_memoryview_obj *)
                                                            original_obj)->typeinfo)) {
        memview = (struct __pyx_memoryview_obj *) original_obj;
        new_memview = NULL;
    } else {
        memview = (struct __pyx_memoryview_obj *) __pyx_memoryview_new(
                                            original_obj, buf_flags, 0, dtype);
        new_memview = memview;
        if (unlikely(!memview))
            goto fail;
    }
    buf = &memview->view;
    if (buf->ndim != ndim) {
        PyErr_Format(PyExc_ValueError,
                "Buffer has wrong number of dimensions (expected %d, got %d)",
                ndim, buf->ndim);
        goto fail;
    }
    if (new_memview) {
        __Pyx_BufFmt_Init(&ctx, stack, dtype);
        if (!__Pyx_BufFmt_CheckString(&ctx, buf->format)) goto fail;
    }
    if ((unsigned) buf->itemsize != dtype->size) {
        PyErr_Format(PyExc_ValueError,
                     "Item size of buffer (%" CYTHON_FORMAT_SSIZE_T "u byte%s) "
                     "does not match size of '%s' (%" CYTHON_FORMAT_SSIZE_T "u byte%s)",
                     buf->itemsize,
                     (buf->itemsize > 1) ? "s" : "",
                     dtype->name,
                     dtype->size,
                     (dtype->size > 1) ? "s" : "");
        goto fail;
    }
    for (i = 0; i < ndim; i++) {
        spec = axes_specs[i];
        if (!__pyx_check_strides(buf, i, ndim, spec))
            goto fail;
        if (!__pyx_check_suboffsets(buf, i, ndim, spec))
            goto fail;
    }
    if (buf->strides && !__pyx_verify_contig(buf, ndim, c_or_f_flag))
        goto fail;
    if (unlikely(__Pyx_init_memviewslice(memview, ndim, memviewslice,
                                         new_memview != NULL) == -1)) {
        goto fail;
    }
    retval = 0;
    goto no_fail;
fail:
    Py_XDECREF(new_memview);
    retval = -1;
no_fail:
    __Pyx_RefNannyFinishContext();
    return retval;
}

static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dcd__nn___pyx_t_5numpy_float32_t(PyObject *obj) {
    __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } };
    __Pyx_BufFmt_StackElem stack[1];
    int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_CONTIG), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_FOLLOW) };
    int retcode;
    if (obj == Py_None) {
        result.memview = (struct __pyx_memoryview_obj *) Py_None;
        return result;
    }
    retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, __Pyx_IS_F_CONTIG,
                                                 (PyBUF_F_CONTIGUOUS | PyBUF_FORMAT | PyBUF_WRITABLE), 2,
                                                 &__Pyx_TypeInfo_nn___pyx_t_5numpy_float32_t, stack,
                                                 &result, obj);
    if (unlikely(retcode == -1))
        goto __pyx_fail;
    return result;
__pyx_fail:
    result.memview = NULL;
    result.data = NULL;
    return result;
}

static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dcd_d__nn___pyx_t_5numpy_float32_t(PyObject *obj) {
    __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } };
    __Pyx_BufFmt_StackElem stack[1];
    int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_CONTIG), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_FOLLOW), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_FOLLOW) };
    int retcode;
    if (obj == Py_None) {
        result.memview = (struct __pyx_memoryview_obj *) Py_None;
        return result;
    }
    retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, __Pyx_IS_F_CONTIG,
                                                 (PyBUF_F_CONTIGUOUS | PyBUF_FORMAT | PyBUF_WRITABLE), 3,
                                                 &__Pyx_TypeInfo_nn___pyx_t_5numpy_float32_t, stack,
                                                 &result, obj);
    if (unlikely(retcode == -1))
        goto __pyx_fail;
    return result;
__pyx_fail:
    result.memview = NULL;
    result.data = NULL;
    return result;
}

static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds_nn___pyx_t_5numpy_float32_t(PyObject *obj) {
    __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } };
    __Pyx_BufFmt_StackElem stack[1];
    int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED) };
    int retcode;
    if (obj == Py_None) {
        result.memview = (struct __pyx_memoryview_obj *) Py_None;
        return result;
    }
    retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, 0,
                                                 PyBUF_RECORDS, 1,
                                                 &__Pyx_TypeInfo_nn___pyx_t_5numpy_float32_t, stack,
                                                 &result, obj);
    if (unlikely(retcode == -1))
        goto __pyx_fail;
    return result;
__pyx_fail:
    result.memview = NULL;
    result.data = NULL;
    return result;
}

#define __PYX_VERIFY_RETURN_INT(target_type, func_type, func_value)       \
    {                                                                     \
        func_type value = func_value;                                     \
        if (sizeof(target_type) < sizeof(func_type)) {                    \
            if (unlikely(value != (func_type) (target_type) value)) {     \
                func_type zero = 0;                                       \
                if (is_unsigned && unlikely(value < zero))                \
                    goto raise_neg_overflow;                              \
                else                                                      \
                    goto raise_overflow;                                  \
            }                                                             \
        }                                                                 \
        return (target_type) value;                                       \
    }

#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
 #if CYTHON_USE_PYLONG_INTERNALS
  #include "longintrepr.h"
 #endif
#endif

static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *x) {
    const int neg_one = (int) -1, const_zero = 0;
    const int is_unsigned = neg_one > const_zero;
#if PY_MAJOR_VERSION < 3
    if (likely(PyInt_Check(x))) {
        if (sizeof(int) < sizeof(long)) {
            __PYX_VERIFY_RETURN_INT(int, long, PyInt_AS_LONG(x))
        } else {
            long val = PyInt_AS_LONG(x);
            if (is_unsigned && unlikely(val < 0)) {
                goto raise_neg_overflow;
            }
            return (int) val;
        }
    } else
#endif
    if (likely(PyLong_Check(x))) {
        if (is_unsigned) {
#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
 #if CYTHON_USE_PYLONG_INTERNALS
            switch (Py_SIZE(x)) {
                case  0: return 0;
                case  1: __PYX_VERIFY_RETURN_INT(int, digit, ((PyLongObject*)x)->ob_digit[0]);
            }
 #endif
#endif
            if (unlikely(Py_SIZE(x) < 0)) {
                goto raise_neg_overflow;
            }
            if (sizeof(int) <= sizeof(unsigned long)) {
                __PYX_VERIFY_RETURN_INT(int, unsigned long, PyLong_AsUnsignedLong(x))
            } else if (sizeof(int) <= sizeof(unsigned long long)) {
                __PYX_VERIFY_RETURN_INT(int, unsigned long long, PyLong_AsUnsignedLongLong(x))
            }
        } else {
#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
 #if CYTHON_USE_PYLONG_INTERNALS
            switch (Py_SIZE(x)) {
                case  0: return 0;
                case  1: __PYX_VERIFY_RETURN_INT(int,  digit, +(((PyLongObject*)x)->ob_digit[0]));
                case -1: __PYX_VERIFY_RETURN_INT(int, sdigit, -(sdigit) ((PyLongObject*)x)->ob_digit[0]);
            }
 #endif
#endif
            if (sizeof(int) <= sizeof(long)) {
                __PYX_VERIFY_RETURN_INT(int, long, PyLong_AsLong(x))
            } else if (sizeof(int) <= sizeof(long long)) {
                __PYX_VERIFY_RETURN_INT(int, long long, PyLong_AsLongLong(x))
            }
        }
        {
#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
            PyErr_SetString(PyExc_RuntimeError,
                            "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
#else
            int val;
            PyObject *v = __Pyx_PyNumber_Int(x);
 #if PY_MAJOR_VERSION < 3
            if (likely(v) && !PyLong_Check(v)) {
                PyObject *tmp = v;
                v = PyNumber_Long(tmp);
                Py_DECREF(tmp);
            }
 #endif
            if (likely(v)) {
                int one = 1; int is_little = (int)*(unsigned char *)&one;
                unsigned char *bytes = (unsigned char *)&val;
                int ret = _PyLong_AsByteArray((PyLongObject *)v,
                                              bytes, sizeof(val),
                                              is_little, !is_unsigned);
                Py_DECREF(v);
                if (likely(!ret))
                    return val;
            }
#endif
            return (int) -1;
        }
    } else {
        int val;
        PyObject *tmp = __Pyx_PyNumber_Int(x);
        if (!tmp) return (int) -1;
        val = __Pyx_PyInt_As_int(tmp);
        Py_DECREF(tmp);
        return val;
    }
raise_overflow:
    PyErr_SetString(PyExc_OverflowError,
        "value too large to convert to int");
    return (int) -1;
raise_neg_overflow:
    PyErr_SetString(PyExc_OverflowError,
        "can't convert negative value to int");
    return (int) -1;
}

static CYTHON_INLINE unsigned int __Pyx_PyInt_As_unsigned_int(PyObject *x) {
    const unsigned int neg_one = (unsigned int) -1, const_zero = 0;
    const int is_unsigned = neg_one > const_zero;
#if PY_MAJOR_VERSION < 3
    if (likely(PyInt_Check(x))) {
        if (sizeof(unsigned int) < sizeof(long)) {
            __PYX_VERIFY_RETURN_INT(unsigned int, long, PyInt_AS_LONG(x))
        } else {
            long val = PyInt_AS_LONG(x);
            if (is_unsigned && unlikely(val < 0)) {
                goto raise_neg_overflow;
            }
            return (unsigned int) val;
        }
    } else
#endif
    if (likely(PyLong_Check(x))) {
        if (is_unsigned) {
#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
 #if CYTHON_USE_PYLONG_INTERNALS
            switch (Py_SIZE(x)) {
                case  0: return 0;
                case  1: __PYX_VERIFY_RETURN_INT(unsigned int, digit, ((PyLongObject*)x)->ob_digit[0]);
            }
 #endif
#endif
            if (unlikely(Py_SIZE(x) < 0)) {
                goto raise_neg_overflow;
            }
            if (sizeof(unsigned int) <= sizeof(unsigned long)) {
                __PYX_VERIFY_RETURN_INT(unsigned int, unsigned long, PyLong_AsUnsignedLong(x))
            } else if (sizeof(unsigned int) <= sizeof(unsigned long long)) {
                __PYX_VERIFY_RETURN_INT(unsigned int, unsigned long long, PyLong_AsUnsignedLongLong(x))
            }
        } else {
#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
 #if CYTHON_USE_PYLONG_INTERNALS
            switch (Py_SIZE(x)) {
                case  0: return 0;
                case  1: __PYX_VERIFY_RETURN_INT(unsigned int,  digit, +(((PyLongObject*)x)->ob_digit[0]));
                case -1: __PYX_VERIFY_RETURN_INT(unsigned int, sdigit, -(sdigit) ((PyLongObject*)x)->ob_digit[0]);
            }
 #endif
#endif
            if (sizeof(unsigned int) <= sizeof(long)) {
                __PYX_VERIFY_RETURN_INT(unsigned int, long, PyLong_AsLong(x))
            } else if (sizeof(unsigned int) <= sizeof(long long)) {
                __PYX_VERIFY_RETURN_INT(unsigned int, long long, PyLong_AsLongLong(x))
            }
        }
        {
#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
            PyErr_SetString(PyExc_RuntimeError,
                            "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
#else
            unsigned int val;
            PyObject *v = __Pyx_PyNumber_Int(x);
 #if PY_MAJOR_VERSION < 3
            if (likely(v) && !PyLong_Check(v)) {
                PyObject *tmp = v;
                v = PyNumber_Long(tmp);
                Py_DECREF(tmp);
            }
 #endif
            if (likely(v)) {
                int one = 1; int is_little = (int)*(unsigned char *)&one;
                unsigned char *bytes = (unsigned char *)&val;
                int ret = _PyLong_AsByteArray((PyLongObject *)v,
                                              bytes, sizeof(val),
                                              is_little, !is_unsigned);
                Py_DECREF(v);
                if (likely(!ret))
                    return val;
            }
#endif
            return (unsigned int) -1;
        }
    } else {
        unsigned int val;
        PyObject *tmp = __Pyx_PyNumber_Int(x);
        if (!tmp) return (unsigned int) -1;
        val = __Pyx_PyInt_As_unsigned_int(tmp);
        Py_DECREF(tmp);
        return val;
    }
raise_overflow:
    PyErr_SetString(PyExc_OverflowError,
        "value too large to convert to unsigned int");
    return (unsigned int) -1;
raise_neg_overflow:
    PyErr_SetString(PyExc_OverflowError,
        "can't convert negative value to unsigned int");
    return (unsigned int) -1;
}

static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dcd____pyx_t_double_complex(PyObject *obj) {
    __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } };
    __Pyx_BufFmt_StackElem stack[1];
    int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_CONTIG), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_FOLLOW) };
    int retcode;
    if (obj == Py_None) {
        result.memview = (struct __pyx_memoryview_obj *) Py_None;
        return result;
    }
    retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, __Pyx_IS_F_CONTIG,
                                                 (PyBUF_F_CONTIGUOUS | PyBUF_FORMAT | PyBUF_WRITABLE), 2,
                                                 &__Pyx_TypeInfo___pyx_t_double_complex, stack,
                                                 &result, obj);
    if (unlikely(retcode == -1))
        goto __pyx_fail;
    return result;
__pyx_fail:
    result.memview = NULL;
    result.data = NULL;
    return result;
}

static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dcd_d____pyx_t_double_complex(PyObject *obj) {
    __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } };
    __Pyx_BufFmt_StackElem stack[1];
    int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_CONTIG), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_FOLLOW), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_FOLLOW) };
    int retcode;
    if (obj == Py_None) {
        result.memview = (struct __pyx_memoryview_obj *) Py_None;
        return result;
    }
    retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, __Pyx_IS_F_CONTIG,
                                                 (PyBUF_F_CONTIGUOUS | PyBUF_FORMAT | PyBUF_WRITABLE), 3,
                                                 &__Pyx_TypeInfo___pyx_t_double_complex, stack,
                                                 &result, obj);
    if (unlikely(retcode == -1))
        goto __pyx_fail;
    return result;
__pyx_fail:
    result.memview = NULL;
    result.data = NULL;
    return result;
}

static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds___pyx_t_double_complex(PyObject *obj) {
    __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } };
    __Pyx_BufFmt_StackElem stack[1];
    int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED) };
    int retcode;
    if (obj == Py_None) {
        result.memview = (struct __pyx_memoryview_obj *) Py_None;
        return result;
    }
    retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, 0,
                                                 PyBUF_RECORDS, 1,
                                                 &__Pyx_TypeInfo___pyx_t_double_complex, stack,
                                                 &result, obj);
    if (unlikely(retcode == -1))
        goto __pyx_fail;
    return result;
__pyx_fail:
    result.memview = NULL;
    result.data = NULL;
    return result;
}

static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dcd__nn___pyx_t_5numpy_float64_t(PyObject *obj) {
    __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } };
    __Pyx_BufFmt_StackElem stack[1];
    int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_CONTIG), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_FOLLOW) };
    int retcode;
    if (obj == Py_None) {
        result.memview = (struct __pyx_memoryview_obj *) Py_None;
        return result;
    }
    retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, __Pyx_IS_F_CONTIG,
                                                 (PyBUF_F_CONTIGUOUS | PyBUF_FORMAT | PyBUF_WRITABLE), 2,
                                                 &__Pyx_TypeInfo_nn___pyx_t_5numpy_float64_t, stack,
                                                 &result, obj);
    if (unlikely(retcode == -1))
        goto __pyx_fail;
    return result;
__pyx_fail:
    result.memview = NULL;
    result.data = NULL;
    return result;
}

static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dcd_d__nn___pyx_t_5numpy_float64_t(PyObject *obj) {
    __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } };
    __Pyx_BufFmt_StackElem stack[1];
    int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_CONTIG), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_FOLLOW), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_FOLLOW) };
    int retcode;
    if (obj == Py_None) {
        result.memview = (struct __pyx_memoryview_obj *) Py_None;
        return result;
    }
    retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, __Pyx_IS_F_CONTIG,
                                                 (PyBUF_F_CONTIGUOUS | PyBUF_FORMAT | PyBUF_WRITABLE), 3,
                                                 &__Pyx_TypeInfo_nn___pyx_t_5numpy_float64_t, stack,
                                                 &result, obj);
    if (unlikely(retcode == -1))
        goto __pyx_fail;
    return result;
__pyx_fail:
    result.memview = NULL;
    result.data = NULL;
    return result;
}

static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds_nn___pyx_t_5numpy_float64_t(PyObject *obj) {
    __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } };
    __Pyx_BufFmt_StackElem stack[1];
    int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED) };
    int retcode;
    if (obj == Py_None) {
        result.memview = (struct __pyx_memoryview_obj *) Py_None;
        return result;
    }
    retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, 0,
                                                 PyBUF_RECORDS, 1,
                                                 &__Pyx_TypeInfo_nn___pyx_t_5numpy_float64_t, stack,
                                                 &result, obj);
    if (unlikely(retcode == -1))
        goto __pyx_fail;
    return result;
__pyx_fail:
    result.memview = NULL;
    result.data = NULL;
    return result;
}

static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dcd____pyx_t_float_complex(PyObject *obj) {
    __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } };
    __Pyx_BufFmt_StackElem stack[1];
    int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_CONTIG), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_FOLLOW) };
    int retcode;
    if (obj == Py_None) {
        result.memview = (struct __pyx_memoryview_obj *) Py_None;
        return result;
    }
    retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, __Pyx_IS_F_CONTIG,
                                                 (PyBUF_F_CONTIGUOUS | PyBUF_FORMAT | PyBUF_WRITABLE), 2,
                                                 &__Pyx_TypeInfo___pyx_t_float_complex, stack,
                                                 &result, obj);
    if (unlikely(retcode == -1))
        goto __pyx_fail;
    return result;
__pyx_fail:
    result.memview = NULL;
    result.data = NULL;
    return result;
}

static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dcd_d____pyx_t_float_complex(PyObject *obj) {
    __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } };
    __Pyx_BufFmt_StackElem stack[1];
    int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_CONTIG), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_FOLLOW), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_FOLLOW) };
    int retcode;
    if (obj == Py_None) {
        result.memview = (struct __pyx_memoryview_obj *) Py_None;
        return result;
    }
    retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, __Pyx_IS_F_CONTIG,
                                                 (PyBUF_F_CONTIGUOUS | PyBUF_FORMAT | PyBUF_WRITABLE), 3,
                                                 &__Pyx_TypeInfo___pyx_t_float_complex, stack,
                                                 &result, obj);
    if (unlikely(retcode == -1))
        goto __pyx_fail;
    return result;
__pyx_fail:
    result.memview = NULL;
    result.data = NULL;
    return result;
}

static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds___pyx_t_float_complex(PyObject *obj) {
    __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } };
    __Pyx_BufFmt_StackElem stack[1];
    int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED) };
    int retcode;
    if (obj == Py_None) {
        result.memview = (struct __pyx_memoryview_obj *) Py_None;
        return result;
    }
    retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, 0,
                                                 PyBUF_RECORDS, 1,
                                                 &__Pyx_TypeInfo___pyx_t_float_complex, stack,
                                                 &result, obj);
    if (unlikely(retcode == -1))
        goto __pyx_fail;
    return result;
__pyx_fail:
    result.memview = NULL;
    result.data = NULL;
    return result;
}

static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value) {
    const int neg_one = (int) -1, const_zero = 0;
    const int is_unsigned = neg_one > const_zero;
    if (is_unsigned) {
        if (sizeof(int) < sizeof(long)) {
            return PyInt_FromLong((long) value);
        } else if (sizeof(int) <= sizeof(unsigned long)) {
            return PyLong_FromUnsignedLong((unsigned long) value);
        } else if (sizeof(int) <= sizeof(unsigned long long)) {
            return PyLong_FromUnsignedLongLong((unsigned long long) value);
        }
    } else {
        if (sizeof(int) <= sizeof(long)) {
            return PyInt_FromLong((long) value);
        } else if (sizeof(int) <= sizeof(long long)) {
            return PyLong_FromLongLong((long long) value);
        }
    }
    {
        int one = 1; int little = (int)*(unsigned char *)&one;
        unsigned char *bytes = (unsigned char *)&value;
        return _PyLong_FromByteArray(bytes, sizeof(int),
                                     little, !is_unsigned);
    }
}

static PyObject *__pyx_memview_get_nn___pyx_t_5numpy_float32_t(const char *itemp) {
    return (PyObject *) PyFloat_FromDouble(*(__pyx_t_5numpy_float32_t *) itemp);
}
static int __pyx_memview_set_nn___pyx_t_5numpy_float32_t(const char *itemp, PyObject *obj) {
    __pyx_t_5numpy_float32_t value = __pyx_PyFloat_AsFloat(obj);
    if ((value == (npy_float32)-1) && PyErr_Occurred())
        return 0;
    *(__pyx_t_5numpy_float32_t *) itemp = value;
    return 1;
}

static PyObject *__pyx_memview_get_int(const char *itemp) {
    return (PyObject *) __Pyx_PyInt_From_int(*(int *) itemp);
}
static int __pyx_memview_set_int(const char *itemp, PyObject *obj) {
    int value = __Pyx_PyInt_As_int(obj);
    if ((value == (int)-1) && PyErr_Occurred())
        return 0;
    *(int *) itemp = value;
    return 1;
}

static CYTHON_INLINE long __Pyx_pow_long(long b, long e) {
    long t = b;
    switch (e) {
        case 3:
            t *= b;
        case 2:
            t *= b;
        case 1:
            return t;
        case 0:
            return 1;
    }
    #if 1
    if (unlikely(e<0)) return 0;
    #endif
    t = 1;
    while (likely(e)) {
        t *= (b * (e&1)) | ((~e)&1);    /* 1 or b */
        b *= b;
        e >>= 1;
    }
    return t;
}

static CYTHON_INLINE PyObject* __Pyx_PyInt_From_unsigned_int(unsigned int value) {
    const unsigned int neg_one = (unsigned int) -1, const_zero = 0;
    const int is_unsigned = neg_one > const_zero;
    if (is_unsigned) {
        if (sizeof(unsigned int) < sizeof(long)) {
            return PyInt_FromLong((long) value);
        } else if (sizeof(unsigned int) <= sizeof(unsigned long)) {
            return PyLong_FromUnsignedLong((unsigned long) value);
        } else if (sizeof(unsigned int) <= sizeof(unsigned long long)) {
            return PyLong_FromUnsignedLongLong((unsigned long long) value);
        }
    } else {
        if (sizeof(unsigned int) <= sizeof(long)) {
            return PyInt_FromLong((long) value);
        } else if (sizeof(unsigned int) <= sizeof(long long)) {
            return PyLong_FromLongLong((long long) value);
        }
    }
    {
        int one = 1; int little = (int)*(unsigned char *)&one;
        unsigned char *bytes = (unsigned char *)&value;
        return _PyLong_FromByteArray(bytes, sizeof(unsigned int),
                                     little, !is_unsigned);
    }
}

static __Pyx_memviewslice
__pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs,
                                 const char *mode, int ndim,
                                 size_t sizeof_dtype, int contig_flag,
                                 int dtype_is_object)
{
    __Pyx_RefNannyDeclarations
    int i;
    __Pyx_memviewslice new_mvs = { 0, 0, { 0 }, { 0 }, { 0 } };
    struct __pyx_memoryview_obj *from_memview = from_mvs->memview;
    Py_buffer *buf = &from_memview->view;
    PyObject *shape_tuple = NULL;
    PyObject *temp_int = NULL;
    struct __pyx_array_obj *array_obj = NULL;
    struct __pyx_memoryview_obj *memview_obj = NULL;
    __Pyx_RefNannySetupContext("__pyx_memoryview_copy_new_contig", 0);
    for (i = 0; i < ndim; i++) {
        if (from_mvs->suboffsets[i] >= 0) {
            PyErr_Format(PyExc_ValueError, "Cannot copy memoryview slice with "
                                           "indirect dimensions (axis %d)", i);
            goto fail;
        }
    }
    shape_tuple = PyTuple_New(ndim);
    if (unlikely(!shape_tuple)) {
        goto fail;
    }
    __Pyx_GOTREF(shape_tuple);
    for(i = 0; i < ndim; i++) {
        temp_int = PyInt_FromSsize_t(from_mvs->shape[i]);
        if(unlikely(!temp_int)) {
            goto fail;
        } else {
            PyTuple_SET_ITEM(shape_tuple, i, temp_int);
            temp_int = NULL;
        }
    }
    array_obj = __pyx_array_new(shape_tuple, sizeof_dtype, buf->format, (char *) mode, NULL);
    if (unlikely(!array_obj)) {
        goto fail;
    }
    __Pyx_GOTREF(array_obj);
    memview_obj = (struct __pyx_memoryview_obj *) __pyx_memoryview_new(
                                    (PyObject *) array_obj, contig_flag,
                                    dtype_is_object,
                                    from_mvs->memview->typeinfo);
    if (unlikely(!memview_obj))
        goto fail;
    if (unlikely(__Pyx_init_memviewslice(memview_obj, ndim, &new_mvs, 1) < 0))
        goto fail;
    if (unlikely(__pyx_memoryview_copy_contents(*from_mvs, new_mvs, ndim, ndim,
                                                dtype_is_object) < 0))
        goto fail;
    goto no_fail;
fail:
    __Pyx_XDECREF(new_mvs.memview);
    new_mvs.memview = NULL;
    new_mvs.data = NULL;
no_fail:
    __Pyx_XDECREF(shape_tuple);
    __Pyx_XDECREF(temp_int);
    __Pyx_XDECREF(array_obj);
    __Pyx_RefNannyFinishContext();
    return new_mvs;
}

static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value) {
    const long neg_one = (long) -1, const_zero = 0;
    const int is_unsigned = neg_one > const_zero;
    if (is_unsigned) {
        if (sizeof(long) < sizeof(long)) {
            return PyInt_FromLong((long) value);
        } else if (sizeof(long) <= sizeof(unsigned long)) {
            return PyLong_FromUnsignedLong((unsigned long) value);
        } else if (sizeof(long) <= sizeof(unsigned long long)) {
            return PyLong_FromUnsignedLongLong((unsigned long long) value);
        }
    } else {
        if (sizeof(long) <= sizeof(long)) {
            return PyInt_FromLong((long) value);
        } else if (sizeof(long) <= sizeof(long long)) {
            return PyLong_FromLongLong((long long) value);
        }
    }
    {
        int one = 1; int little = (int)*(unsigned char *)&one;
        unsigned char *bytes = (unsigned char *)&value;
        return _PyLong_FromByteArray(bytes, sizeof(long),
                                     little, !is_unsigned);
    }
}

#if CYTHON_CCOMPLEX
  #ifdef __cplusplus
    static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) {
      return ::std::complex< double >(x, y);
    }
  #else
    static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) {
      return x + y*(__pyx_t_double_complex)_Complex_I;
    }
  #endif
#else
    static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) {
      __pyx_t_double_complex z;
      z.real = x;
      z.imag = y;
      return z;
    }
#endif

static __pyx_t_double_complex __Pyx_PyComplex_As___pyx_t_double_complex(PyObject* o) {
    Py_complex cval;
#if CYTHON_COMPILING_IN_CPYTHON
    if (PyComplex_CheckExact(o))
        cval = ((PyComplexObject *)o)->cval;
    else
#endif
        cval = PyComplex_AsCComplex(o);
    return __pyx_t_double_complex_from_parts(
               (double)cval.real,
               (double)cval.imag);
}

static PyObject *__pyx_memview_get___pyx_t_double_complex(const char *itemp) {
    return (PyObject *) __pyx_PyComplex_FromComplex(*(__pyx_t_double_complex *) itemp);
}
static int __pyx_memview_set___pyx_t_double_complex(const char *itemp, PyObject *obj) {
    __pyx_t_double_complex value = __Pyx_PyComplex_As___pyx_t_double_complex(obj);
    if (PyErr_Occurred())
        return 0;
    *(__pyx_t_double_complex *) itemp = value;
    return 1;
}

#if CYTHON_CCOMPLEX
#else
    static CYTHON_INLINE int __Pyx_c_eq(__pyx_t_double_complex a, __pyx_t_double_complex b) {
       return (a.real == b.real) && (a.imag == b.imag);
    }
    static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum(__pyx_t_double_complex a, __pyx_t_double_complex b) {
        __pyx_t_double_complex z;
        z.real = a.real + b.real;
        z.imag = a.imag + b.imag;
        return z;
    }
    static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff(__pyx_t_double_complex a, __pyx_t_double_complex b) {
        __pyx_t_double_complex z;
        z.real = a.real - b.real;
        z.imag = a.imag - b.imag;
        return z;
    }
    static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod(__pyx_t_double_complex a, __pyx_t_double_complex b) {
        __pyx_t_double_complex z;
        z.real = a.real * b.real - a.imag * b.imag;
        z.imag = a.real * b.imag + a.imag * b.real;
        return z;
    }
    static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot(__pyx_t_double_complex a, __pyx_t_double_complex b) {
        __pyx_t_double_complex z;
        double denom = b.real * b.real + b.imag * b.imag;
        z.real = (a.real * b.real + a.imag * b.imag) / denom;
        z.imag = (a.imag * b.real - a.real * b.imag) / denom;
        return z;
    }
    static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg(__pyx_t_double_complex a) {
        __pyx_t_double_complex z;
        z.real = -a.real;
        z.imag = -a.imag;
        return z;
    }
    static CYTHON_INLINE int __Pyx_c_is_zero(__pyx_t_double_complex a) {
       return (a.real == 0) && (a.imag == 0);
    }
    static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj(__pyx_t_double_complex a) {
        __pyx_t_double_complex z;
        z.real =  a.real;
        z.imag = -a.imag;
        return z;
    }
    #if 1
        static CYTHON_INLINE double __Pyx_c_abs(__pyx_t_double_complex z) {
          #if !defined(HAVE_HYPOT) || defined(_MSC_VER)
            return sqrt(z.real*z.real + z.imag*z.imag);
          #else
            return hypot(z.real, z.imag);
          #endif
        }
        static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_pow(__pyx_t_double_complex a, __pyx_t_double_complex b) {
            __pyx_t_double_complex z;
            double r, lnr, theta, z_r, z_theta;
            if (b.imag == 0 && b.real == (int)b.real) {
                if (b.real < 0) {
                    double denom = a.real * a.real + a.imag * a.imag;
                    a.real = a.real / denom;
                    a.imag = -a.imag / denom;
                    b.real = -b.real;
                }
                switch ((int)b.real) {
                    case 0:
                        z.real = 1;
                        z.imag = 0;
                        return z;
                    case 1:
                        return a;
                    case 2:
                        z = __Pyx_c_prod(a, a);
                        return __Pyx_c_prod(a, a);
                    case 3:
                        z = __Pyx_c_prod(a, a);
                        return __Pyx_c_prod(z, a);
                    case 4:
                        z = __Pyx_c_prod(a, a);
                        return __Pyx_c_prod(z, z);
                }
            }
            if (a.imag == 0) {
                if (a.real == 0) {
                    return a;
                }
                r = a.real;
                theta = 0;
            } else {
                r = __Pyx_c_abs(a);
                theta = atan2(a.imag, a.real);
            }
            lnr = log(r);
            z_r = exp(lnr * b.real - theta * b.imag);
            z_theta = theta * b.real + lnr * b.imag;
            z.real = z_r * cos(z_theta);
            z.imag = z_r * sin(z_theta);
            return z;
        }
    #endif
#endif

static PyObject *__pyx_memview_get_nn___pyx_t_5numpy_float64_t(const char *itemp) {
    return (PyObject *) PyFloat_FromDouble(*(__pyx_t_5numpy_float64_t *) itemp);
}
static int __pyx_memview_set_nn___pyx_t_5numpy_float64_t(const char *itemp, PyObject *obj) {
    __pyx_t_5numpy_float64_t value = __pyx_PyFloat_AsDouble(obj);
    if ((value == (npy_float64)-1) && PyErr_Occurred())
        return 0;
    *(__pyx_t_5numpy_float64_t *) itemp = value;
    return 1;
}

#if CYTHON_CCOMPLEX
  #ifdef __cplusplus
    static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) {
      return ::std::complex< float >(x, y);
    }
  #else
    static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) {
      return x + y*(__pyx_t_float_complex)_Complex_I;
    }
  #endif
#else
    static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) {
      __pyx_t_float_complex z;
      z.real = x;
      z.imag = y;
      return z;
    }
#endif

static __pyx_t_float_complex __Pyx_PyComplex_As___pyx_t_float_complex(PyObject* o) {
    Py_complex cval;
#if CYTHON_COMPILING_IN_CPYTHON
    if (PyComplex_CheckExact(o))
        cval = ((PyComplexObject *)o)->cval;
    else
#endif
        cval = PyComplex_AsCComplex(o);
    return __pyx_t_float_complex_from_parts(
               (float)cval.real,
               (float)cval.imag);
}

static PyObject *__pyx_memview_get___pyx_t_float_complex(const char *itemp) {
    return (PyObject *) __pyx_PyComplex_FromComplex(*(__pyx_t_float_complex *) itemp);
}
static int __pyx_memview_set___pyx_t_float_complex(const char *itemp, PyObject *obj) {
    __pyx_t_float_complex value = __Pyx_PyComplex_As___pyx_t_float_complex(obj);
    if (PyErr_Occurred())
        return 0;
    *(__pyx_t_float_complex *) itemp = value;
    return 1;
}

#if CYTHON_CCOMPLEX
#else
    static CYTHON_INLINE int __Pyx_c_eqf(__pyx_t_float_complex a, __pyx_t_float_complex b) {
       return (a.real == b.real) && (a.imag == b.imag);
    }
    static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sumf(__pyx_t_float_complex a, __pyx_t_float_complex b) {
        __pyx_t_float_complex z;
        z.real = a.real + b.real;
        z.imag = a.imag + b.imag;
        return z;
    }
    static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_difff(__pyx_t_float_complex a, __pyx_t_float_complex b) {
        __pyx_t_float_complex z;
        z.real = a.real - b.real;
        z.imag = a.imag - b.imag;
        return z;
    }
    static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prodf(__pyx_t_float_complex a, __pyx_t_float_complex b) {
        __pyx_t_float_complex z;
        z.real = a.real * b.real - a.imag * b.imag;
        z.imag = a.real * b.imag + a.imag * b.real;
        return z;
    }
    static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quotf(__pyx_t_float_complex a, __pyx_t_float_complex b) {
        __pyx_t_float_complex z;
        float denom = b.real * b.real + b.imag * b.imag;
        z.real = (a.real * b.real + a.imag * b.imag) / denom;
        z.imag = (a.imag * b.real - a.real * b.imag) / denom;
        return z;
    }
    static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_negf(__pyx_t_float_complex a) {
        __pyx_t_float_complex z;
        z.real = -a.real;
        z.imag = -a.imag;
        return z;
    }
    static CYTHON_INLINE int __Pyx_c_is_zerof(__pyx_t_float_complex a) {
       return (a.real == 0) && (a.imag == 0);
    }
    static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conjf(__pyx_t_float_complex a) {
        __pyx_t_float_complex z;
        z.real =  a.real;
        z.imag = -a.imag;
        return z;
    }
    #if 1
        static CYTHON_INLINE float __Pyx_c_absf(__pyx_t_float_complex z) {
          #if !defined(HAVE_HYPOT) || defined(_MSC_VER)
            return sqrtf(z.real*z.real + z.imag*z.imag);
          #else
            return hypotf(z.real, z.imag);
          #endif
        }
        static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_powf(__pyx_t_float_complex a, __pyx_t_float_complex b) {
            __pyx_t_float_complex z;
            float r, lnr, theta, z_r, z_theta;
            if (b.imag == 0 && b.real == (int)b.real) {
                if (b.real < 0) {
                    float denom = a.real * a.real + a.imag * a.imag;
                    a.real = a.real / denom;
                    a.imag = -a.imag / denom;
                    b.real = -b.real;
                }
                switch ((int)b.real) {
                    case 0:
                        z.real = 1;
                        z.imag = 0;
                        return z;
                    case 1:
                        return a;
                    case 2:
                        z = __Pyx_c_prodf(a, a);
                        return __Pyx_c_prodf(a, a);
                    case 3:
                        z = __Pyx_c_prodf(a, a);
                        return __Pyx_c_prodf(z, a);
                    case 4:
                        z = __Pyx_c_prodf(a, a);
                        return __Pyx_c_prodf(z, z);
                }
            }
            if (a.imag == 0) {
                if (a.real == 0) {
                    return a;
                }
                r = a.real;
                theta = 0;
            } else {
                r = __Pyx_c_absf(a);
                theta = atan2f(a.imag, a.real);
            }
            lnr = logf(r);
            z_r = expf(lnr * b.real - theta * b.imag);
            z_theta = theta * b.real + lnr * b.imag;
            z.real = z_r * cosf(z_theta);
            z.imag = z_r * sinf(z_theta);
            return z;
        }
    #endif
#endif

static int
__pyx_memviewslice_is_contig(const __Pyx_memviewslice *mvs,
                             char order, int ndim)
{
    int i, index, step, start;
    Py_ssize_t itemsize = mvs->memview->view.itemsize;
    if (order == 'F') {
        step = 1;
        start = 0;
    } else {
        step = -1;
        start = ndim - 1;
    }
    for (i = 0; i < ndim; i++) {
        index = start + step * i;
        if (mvs->suboffsets[index] >= 0 || mvs->strides[index] != itemsize)
            return 0;
        itemsize *= mvs->shape[index];
    }
    return 1;
}

static void
__pyx_get_array_memory_extents(__Pyx_memviewslice *slice,
                               void **out_start, void **out_end,
                               int ndim, size_t itemsize)
{
    char *start, *end;
    int i;
    start = end = slice->data;
    for (i = 0; i < ndim; i++) {
        Py_ssize_t stride = slice->strides[i];
        Py_ssize_t extent = slice->shape[i];
        if (extent == 0) {
            *out_start = *out_end = start;
            return;
        } else {
            if (stride > 0)
                end += stride * (extent - 1);
            else
                start += stride * (extent - 1);
        }
    }
    *out_start = start;
    *out_end = end + itemsize;
}
static int
__pyx_slices_overlap(__Pyx_memviewslice *slice1,
                     __Pyx_memviewslice *slice2,
                     int ndim, size_t itemsize)
{
    void *start1, *end1, *start2, *end2;
    __pyx_get_array_memory_extents(slice1, &start1, &end1, ndim, itemsize);
    __pyx_get_array_memory_extents(slice2, &start2, &end2, ndim, itemsize);
    return (start1 < end2) && (start2 < end1);
}

static CYTHON_INLINE PyObject *
__pyx_capsule_create(void *p, CYTHON_UNUSED const char *sig)
{
    PyObject *cobj;
#if PY_VERSION_HEX >= 0x02070000
    cobj = PyCapsule_New(p, sig, NULL);
#else
    cobj = PyCObject_FromVoidPtr(p, NULL);
#endif
    return cobj;
}

static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *x) {
    const char neg_one = (char) -1, const_zero = 0;
    const int is_unsigned = neg_one > const_zero;
#if PY_MAJOR_VERSION < 3
    if (likely(PyInt_Check(x))) {
        if (sizeof(char) < sizeof(long)) {
            __PYX_VERIFY_RETURN_INT(char, long, PyInt_AS_LONG(x))
        } else {
            long val = PyInt_AS_LONG(x);
            if (is_unsigned && unlikely(val < 0)) {
                goto raise_neg_overflow;
            }
            return (char) val;
        }
    } else
#endif
    if (likely(PyLong_Check(x))) {
        if (is_unsigned) {
#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
 #if CYTHON_USE_PYLONG_INTERNALS
            switch (Py_SIZE(x)) {
                case  0: return 0;
                case  1: __PYX_VERIFY_RETURN_INT(char, digit, ((PyLongObject*)x)->ob_digit[0]);
            }
 #endif
#endif
            if (unlikely(Py_SIZE(x) < 0)) {
                goto raise_neg_overflow;
            }
            if (sizeof(char) <= sizeof(unsigned long)) {
                __PYX_VERIFY_RETURN_INT(char, unsigned long, PyLong_AsUnsignedLong(x))
            } else if (sizeof(char) <= sizeof(unsigned long long)) {
                __PYX_VERIFY_RETURN_INT(char, unsigned long long, PyLong_AsUnsignedLongLong(x))
            }
        } else {
#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
 #if CYTHON_USE_PYLONG_INTERNALS
            switch (Py_SIZE(x)) {
                case  0: return 0;
                case  1: __PYX_VERIFY_RETURN_INT(char,  digit, +(((PyLongObject*)x)->ob_digit[0]));
                case -1: __PYX_VERIFY_RETURN_INT(char, sdigit, -(sdigit) ((PyLongObject*)x)->ob_digit[0]);
            }
 #endif
#endif
            if (sizeof(char) <= sizeof(long)) {
                __PYX_VERIFY_RETURN_INT(char, long, PyLong_AsLong(x))
            } else if (sizeof(char) <= sizeof(long long)) {
                __PYX_VERIFY_RETURN_INT(char, long long, PyLong_AsLongLong(x))
            }
        }
        {
#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
            PyErr_SetString(PyExc_RuntimeError,
                            "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
#else
            char val;
            PyObject *v = __Pyx_PyNumber_Int(x);
 #if PY_MAJOR_VERSION < 3
            if (likely(v) && !PyLong_Check(v)) {
                PyObject *tmp = v;
                v = PyNumber_Long(tmp);
                Py_DECREF(tmp);
            }
 #endif
            if (likely(v)) {
                int one = 1; int is_little = (int)*(unsigned char *)&one;
                unsigned char *bytes = (unsigned char *)&val;
                int ret = _PyLong_AsByteArray((PyLongObject *)v,
                                              bytes, sizeof(val),
                                              is_little, !is_unsigned);
                Py_DECREF(v);
                if (likely(!ret))
                    return val;
            }
#endif
            return (char) -1;
        }
    } else {
        char val;
        PyObject *tmp = __Pyx_PyNumber_Int(x);
        if (!tmp) return (char) -1;
        val = __Pyx_PyInt_As_char(tmp);
        Py_DECREF(tmp);
        return val;
    }
raise_overflow:
    PyErr_SetString(PyExc_OverflowError,
        "value too large to convert to char");
    return (char) -1;
raise_neg_overflow:
    PyErr_SetString(PyExc_OverflowError,
        "can't convert negative value to char");
    return (char) -1;
}

static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *x) {
    const long neg_one = (long) -1, const_zero = 0;
    const int is_unsigned = neg_one > const_zero;
#if PY_MAJOR_VERSION < 3
    if (likely(PyInt_Check(x))) {
        if (sizeof(long) < sizeof(long)) {
            __PYX_VERIFY_RETURN_INT(long, long, PyInt_AS_LONG(x))
        } else {
            long val = PyInt_AS_LONG(x);
            if (is_unsigned && unlikely(val < 0)) {
                goto raise_neg_overflow;
            }
            return (long) val;
        }
    } else
#endif
    if (likely(PyLong_Check(x))) {
        if (is_unsigned) {
#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
 #if CYTHON_USE_PYLONG_INTERNALS
            switch (Py_SIZE(x)) {
                case  0: return 0;
                case  1: __PYX_VERIFY_RETURN_INT(long, digit, ((PyLongObject*)x)->ob_digit[0]);
            }
 #endif
#endif
            if (unlikely(Py_SIZE(x) < 0)) {
                goto raise_neg_overflow;
            }
            if (sizeof(long) <= sizeof(unsigned long)) {
                __PYX_VERIFY_RETURN_INT(long, unsigned long, PyLong_AsUnsignedLong(x))
            } else if (sizeof(long) <= sizeof(unsigned long long)) {
                __PYX_VERIFY_RETURN_INT(long, unsigned long long, PyLong_AsUnsignedLongLong(x))
            }
        } else {
#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
 #if CYTHON_USE_PYLONG_INTERNALS
            switch (Py_SIZE(x)) {
                case  0: return 0;
                case  1: __PYX_VERIFY_RETURN_INT(long,  digit, +(((PyLongObject*)x)->ob_digit[0]));
                case -1: __PYX_VERIFY_RETURN_INT(long, sdigit, -(sdigit) ((PyLongObject*)x)->ob_digit[0]);
            }
 #endif
#endif
            if (sizeof(long) <= sizeof(long)) {
                __PYX_VERIFY_RETURN_INT(long, long, PyLong_AsLong(x))
            } else if (sizeof(long) <= sizeof(long long)) {
                __PYX_VERIFY_RETURN_INT(long, long long, PyLong_AsLongLong(x))
            }
        }
        {
#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
            PyErr_SetString(PyExc_RuntimeError,
                            "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
#else
            long val;
            PyObject *v = __Pyx_PyNumber_Int(x);
 #if PY_MAJOR_VERSION < 3
            if (likely(v) && !PyLong_Check(v)) {
                PyObject *tmp = v;
                v = PyNumber_Long(tmp);
                Py_DECREF(tmp);
            }
 #endif
            if (likely(v)) {
                int one = 1; int is_little = (int)*(unsigned char *)&one;
                unsigned char *bytes = (unsigned char *)&val;
                int ret = _PyLong_AsByteArray((PyLongObject *)v,
                                              bytes, sizeof(val),
                                              is_little, !is_unsigned);
                Py_DECREF(v);
                if (likely(!ret))
                    return val;
            }
#endif
            return (long) -1;
        }
    } else {
        long val;
        PyObject *tmp = __Pyx_PyNumber_Int(x);
        if (!tmp) return (long) -1;
        val = __Pyx_PyInt_As_long(tmp);
        Py_DECREF(tmp);
        return val;
    }
raise_overflow:
    PyErr_SetString(PyExc_OverflowError,
        "value too large to convert to long");
    return (long) -1;
raise_neg_overflow:
    PyErr_SetString(PyExc_OverflowError,
        "can't convert negative value to long");
    return (long) -1;
}

static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dcd__int(PyObject *obj) {
    __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } };
    __Pyx_BufFmt_StackElem stack[1];
    int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_CONTIG), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_FOLLOW) };
    int retcode;
    if (obj == Py_None) {
        result.memview = (struct __pyx_memoryview_obj *) Py_None;
        return result;
    }
    retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, __Pyx_IS_F_CONTIG,
                                                 (PyBUF_F_CONTIGUOUS | PyBUF_FORMAT | PyBUF_WRITABLE), 2,
                                                 &__Pyx_TypeInfo_int, stack,
                                                 &result, obj);
    if (unlikely(retcode == -1))
        goto __pyx_fail;
    return result;
__pyx_fail:
    result.memview = NULL;
    result.data = NULL;
    return result;
}

static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds_int(PyObject *obj) {
    __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } };
    __Pyx_BufFmt_StackElem stack[1];
    int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED) };
    int retcode;
    if (obj == Py_None) {
        result.memview = (struct __pyx_memoryview_obj *) Py_None;
        return result;
    }
    retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, 0,
                                                 PyBUF_RECORDS, 1,
                                                 &__Pyx_TypeInfo_int, stack,
                                                 &result, obj);
    if (unlikely(retcode == -1))
        goto __pyx_fail;
    return result;
__pyx_fail:
    result.memview = NULL;
    result.data = NULL;
    return result;
}

static int __Pyx_check_binary_version(void) {
    char ctversion[4], rtversion[4];
    PyOS_snprintf(ctversion, 4, "%d.%d", PY_MAJOR_VERSION, PY_MINOR_VERSION);
    PyOS_snprintf(rtversion, 4, "%s", Py_GetVersion());
    if (ctversion[0] != rtversion[0] || ctversion[2] != rtversion[2]) {
        char message[200];
        PyOS_snprintf(message, sizeof(message),
                      "compiletime version %s of module '%.100s' "
                      "does not match runtime version %s",
                      ctversion, __Pyx_MODULE_NAME, rtversion);
        return PyErr_WarnEx(NULL, message, 1);
    }
    return 0;
}

#ifndef __PYX_HAVE_RT_ImportModule
#define __PYX_HAVE_RT_ImportModule
static PyObject *__Pyx_ImportModule(const char *name) {
    PyObject *py_name = 0;
    PyObject *py_module = 0;
    py_name = __Pyx_PyIdentifier_FromString(name);
    if (!py_name)
        goto bad;
    py_module = PyImport_Import(py_name);
    Py_DECREF(py_name);
    return py_module;
bad:
    Py_XDECREF(py_name);
    return 0;
}
#endif

#ifndef __PYX_HAVE_RT_ImportType
#define __PYX_HAVE_RT_ImportType
static PyTypeObject *__Pyx_ImportType(const char *module_name, const char *class_name,
    size_t size, int strict)
{
    PyObject *py_module = 0;
    PyObject *result = 0;
    PyObject *py_name = 0;
    char warning[200];
    Py_ssize_t basicsize;
#ifdef Py_LIMITED_API
    PyObject *py_basicsize;
#endif
    py_module = __Pyx_ImportModule(module_name);
    if (!py_module)
        goto bad;
    py_name = __Pyx_PyIdentifier_FromString(class_name);
    if (!py_name)
        goto bad;
    result = PyObject_GetAttr(py_module, py_name);
    Py_DECREF(py_name);
    py_name = 0;
    Py_DECREF(py_module);
    py_module = 0;
    if (!result)
        goto bad;
    if (!PyType_Check(result)) {
        PyErr_Format(PyExc_TypeError,
            "%.200s.%.200s is not a type object",
            module_name, class_name);
        goto bad;
    }
#ifndef Py_LIMITED_API
    basicsize = ((PyTypeObject *)result)->tp_basicsize;
#else
    py_basicsize = PyObject_GetAttrString(result, "__basicsize__");
    if (!py_basicsize)
        goto bad;
    basicsize = PyLong_AsSsize_t(py_basicsize);
    Py_DECREF(py_basicsize);
    py_basicsize = 0;
    if (basicsize == (Py_ssize_t)-1 && PyErr_Occurred())
        goto bad;
#endif
    if (!strict && (size_t)basicsize > size) {
        PyOS_snprintf(warning, sizeof(warning),
            "%s.%s size changed, may indicate binary incompatibility",
            module_name, class_name);
        if (PyErr_WarnEx(NULL, warning, 0) < 0) goto bad;
    }
    else if ((size_t)basicsize != size) {
        PyErr_Format(PyExc_ValueError,
            "%.200s.%.200s has the wrong size, try recompiling",
            module_name, class_name);
        goto bad;
    }
    return (PyTypeObject *)result;
bad:
    Py_XDECREF(py_module);
    Py_XDECREF(result);
    return NULL;
}
#endif

static int __Pyx_InitStrings(__Pyx_StringTabEntry *t) {
    while (t->p) {
        #if PY_MAJOR_VERSION < 3
        if (t->is_unicode) {
            *t->p = PyUnicode_DecodeUTF8(t->s, t->n - 1, NULL);
        } else if (t->intern) {
            *t->p = PyString_InternFromString(t->s);
        } else {
            *t->p = PyString_FromStringAndSize(t->s, t->n - 1);
        }
        #else
        if (t->is_unicode | t->is_str) {
            if (t->intern) {
                *t->p = PyUnicode_InternFromString(t->s);
            } else if (t->encoding) {
                *t->p = PyUnicode_Decode(t->s, t->n - 1, t->encoding, NULL);
            } else {
                *t->p = PyUnicode_FromStringAndSize(t->s, t->n - 1);
            }
        } else {
            *t->p = PyBytes_FromStringAndSize(t->s, t->n - 1);
        }
        #endif
        if (!*t->p)
            return -1;
        ++t;
    }
    return 0;
}

static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char* c_str) {
    return __Pyx_PyUnicode_FromStringAndSize(c_str, (Py_ssize_t)strlen(c_str));
}
static CYTHON_INLINE char* __Pyx_PyObject_AsString(PyObject* o) {
    Py_ssize_t ignore;
    return __Pyx_PyObject_AsStringAndSize(o, &ignore);
}
static CYTHON_INLINE char* __Pyx_PyObject_AsStringAndSize(PyObject* o, Py_ssize_t *length) {
#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT
    if (
#if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII
            __Pyx_sys_getdefaultencoding_not_ascii &&
#endif
            PyUnicode_Check(o)) {
#if PY_VERSION_HEX < 0x03030000
        char* defenc_c;
        PyObject* defenc = _PyUnicode_AsDefaultEncodedString(o, NULL);
        if (!defenc) return NULL;
        defenc_c = PyBytes_AS_STRING(defenc);
#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII
        {
            char* end = defenc_c + PyBytes_GET_SIZE(defenc);
            char* c;
            for (c = defenc_c; c < end; c++) {
                if ((unsigned char) (*c) >= 128) {
                    PyUnicode_AsASCIIString(o);
                    return NULL;
                }
            }
        }
#endif
        *length = PyBytes_GET_SIZE(defenc);
        return defenc_c;
#else
        if (__Pyx_PyUnicode_READY(o) == -1) return NULL;
#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII
        if (PyUnicode_IS_ASCII(o)) {
            *length = PyUnicode_GET_LENGTH(o);
            return PyUnicode_AsUTF8(o);
        } else {
            PyUnicode_AsASCIIString(o);
            return NULL;
        }
#else
        return PyUnicode_AsUTF8AndSize(o, length);
#endif
#endif
    } else
#endif
#if !CYTHON_COMPILING_IN_PYPY
    if (PyByteArray_Check(o)) {
        *length = PyByteArray_GET_SIZE(o);
        return PyByteArray_AS_STRING(o);
    } else
#endif
    {
        char* result;
        int r = PyBytes_AsStringAndSize(o, &result, length);
        if (unlikely(r < 0)) {
            return NULL;
        } else {
            return result;
        }
    }
}
static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject* x) {
   int is_true = x == Py_True;
   if (is_true | (x == Py_False) | (x == Py_None)) return is_true;
   else return PyObject_IsTrue(x);
}
static CYTHON_INLINE PyObject* __Pyx_PyNumber_Int(PyObject* x) {
  PyNumberMethods *m;
  const char *name = NULL;
  PyObject *res = NULL;
#if PY_MAJOR_VERSION < 3
  if (PyInt_Check(x) || PyLong_Check(x))
#else
  if (PyLong_Check(x))
#endif
    return Py_INCREF(x), x;
  m = Py_TYPE(x)->tp_as_number;
#if PY_MAJOR_VERSION < 3
  if (m && m->nb_int) {
    name = "int";
    res = PyNumber_Int(x);
  }
  else if (m && m->nb_long) {
    name = "long";
    res = PyNumber_Long(x);
  }
#else
  if (m && m->nb_int) {
    name = "int";
    res = PyNumber_Long(x);
  }
#endif
  if (res) {
#if PY_MAJOR_VERSION < 3
    if (!PyInt_Check(res) && !PyLong_Check(res)) {
#else
    if (!PyLong_Check(res)) {
#endif
      PyErr_Format(PyExc_TypeError,
                   "__%.4s__ returned non-%.4s (type %.200s)",
                   name, name, Py_TYPE(res)->tp_name);
      Py_DECREF(res);
      return NULL;
    }
  }
  else if (!PyErr_Occurred()) {
    PyErr_SetString(PyExc_TypeError,
                    "an integer is required");
  }
  return res;
}
static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject* b) {
  Py_ssize_t ival;
  PyObject *x;
#if PY_MAJOR_VERSION < 3
  if (likely(PyInt_CheckExact(b)))
      return PyInt_AS_LONG(b);
#endif
  if (likely(PyLong_CheckExact(b))) {
    #if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
     #if CYTHON_USE_PYLONG_INTERNALS
       switch (Py_SIZE(b)) {
       case -1: return -(sdigit)((PyLongObject*)b)->ob_digit[0];
       case  0: return 0;
       case  1: return ((PyLongObject*)b)->ob_digit[0];
       }
     #endif
    #endif
    return PyLong_AsSsize_t(b);
  }
  x = PyNumber_Index(b);
  if (!x) return -1;
  ival = PyInt_AsSsize_t(x);
  Py_DECREF(x);
  return ival;
}
static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t ival) {
    return PyInt_FromSize_t(ival);
}


#endif /* Py_PYTHON_H */
