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StatsForecastAutoETS

API referenceSource
Categorical in XInsamplePred intPred int insample

StatsForecast Automatic Exponential Smoothing model.

Quickstart

python
from sktime.forecasting.statsforecast import StatsForecastAutoETS

estimator = StatsForecastAutoETS(season_length: int=1, model: str='ZZZ', damped: bool | None=None, phi: float | None=None)

Parameters(4)

season_lengthint, optional (default=1)
Number of observations per unit of time. Ex: 24 Hourly data.
modelstr, optional (default=”ZZZ”)
Controlling state-space-equations.
dampedbool, optional (default=None)
A parameter that ‘dampens’ the trend.
phifloat, optional (default=None)

Smoothing parameter for trend damping. Only used when damped=True.

References

  1. [1 ] https://nixtlaverse.nixtla.io/statsforecast/src/core/models.html#autoets [2 ] https://github.com/robjhyndman/forecast