Forecaster
StatsForecastAutoTBATS
StatsForecast TBATS model.
Quickstart
python
from sktime.forecasting.statsforecast import StatsForecastAutoTBATS
estimator = StatsForecastAutoTBATS(seasonal_periods: int | list [int ]=1, use_boxcox: bool | None=None, use_trend: bool | None=None, use_damped_trend: bool | None=None, use_arma_errors: bool=True, bc_lower_bound: float=0.0, bc_upper_bound: float=1.0)Parameters(7)
- seasonal_periodsint or list of int. (default=1)
- Number of observations per unit of time. Ex: 24 Hourly data.
- use_boxcoxbool (default=None)
- Whether or not to use a Box-Cox transformation. By default tries both.
- use_trendbool (default=None)
- Whether or not to use a trend component. By default tries both.
- use_damped_trendbool (default=None)
- Whether or not to dampen the trend component. By default tries both.
- use_arma_errorsbool (default=True)
- Whether or not to use a ARMA errors. Default is True and this evaluates both models.
- bc_lower_boundfloat (default=0.0)
- Lower bound for the Box-Cox transformation.
- bc_upper_boundfloat (default=1.0)
- Upper bound for the Box-Cox transformation.
References
- [1 ] https://nixtlaverse.nixtla.io/statsforecast/src/core/models.html#autotbats