parent_command:forecast
usage: autoselect [--naive] [-d {AAPL}] [-c TARGET_COLUMN] [-n N_DAYS] [-s {N,A,M}] [-p SEASONAL_PERIODS] [-w START_WINDOW] [--end S_END_DATE] [--start S_START_DATE] [--residuals] [--forecast-only] [--export-pred-raw]

Perform Automatic Statistical Forecast (select best statistical model from AutoARIMA, AutoETS, AutoCES, MSTL, ...)

optional arguments:
  --naive               Show the naive baseline for a model. (default: False)
  -d {AAPL}, --dataset {AAPL}
                        The name of the dataset you want to select (default: None)
  -c TARGET_COLUMN, --target-column TARGET_COLUMN
                        The name of the specific column you want to use (default: close)
  -n N_DAYS, --n-days N_DAYS
                        prediction days. (default: 5)
  -s {N,A,M}, --seasonal {N,A,M}
                        Seasonality: N: None, A: Additive, M: Multiplicative. (default: A)
  -p SEASONAL_PERIODS, --periods SEASONAL_PERIODS
                        Seasonal periods: 4: Quarterly, 7: Daily (default: 7)
  -w START_WINDOW, --window START_WINDOW
                        Start point for rolling training and forecast window. 0.0-1.0 (default: 0.85)
  --end S_END_DATE      The end date (format YYYY-MM-DD) to select for testing (default: None)
  --start S_START_DATE  The start date (format YYYY-MM-DD) to select for testing (default: None)
  --residuals           Show the residuals for the model. (default: False)
  --forecast-only       Do not plot the historical data without forecasts. (default: False)
  --export-pred-raw     Export predictions to a csv file. (default: False)


Examples:
- Perform an automatic statistical forecast for the selected dataset: forecast/autoselect -d {AAPL}
- Predict the next 10 days using the best statistical model: forecast/autoselect -n 10
- Forecast using a specific target column and seasonal periods: forecast/autoselect -c TARGET_COLUMN -p 4
- Perform an automatic forecast with a custom start and end date: forecast/autoselect --start 2022-01-01 --end 2022-12-31
- Show the naive baseline for a model: forecast/autoselect --naive
- Use a specific seasonality type and rolling training window: forecast/autoselect -s M -w 0.9
- Display the residuals for the chosen model: forecast/autoselect --residuals
- Plot only the forecast without historical data: forecast/autoselect --forecast-only
- Export the predictions to a CSV file: forecast/autoselect --export-pred-raw