StatsForecastAutoThetaModel

class StatsForecastAutoThetaModel(season_length: int = 1, decomposition_type: str = 'multiplicative', model: Optional[str] = None)

Bases: etna.models.mixins.PerSegmentModelMixin, etna.models.mixins.PredictionIntervalContextIgnorantModelMixin, etna.models.base.PredictionIntervalContextIgnorantAbstractModel

Class for holding statsforecast.models.AutoTheta.

Documentation for the underlying model.

Method forecast only works on ouf-of-sample data that goes right after training data.

Method predict only works on in-sample data.

Init model with given params.

Parameters

• season_length (int) – Number of observations per unit of time. Ex: 24 Hourly data.

• decomposition_type (str) – Sesonal decomposition type, ‘multiplicative’ (default) or ‘additive’.

• model (Optional[str]) – Controlling Theta Model. By default searches the best model.

Inherited-members

Methods

fit(ts)	Fit model.
forecast(ts[, prediction_interval, ...])	Make predictions.
get_model()	Get internal models that are used inside etna class.
load(path)	Load an object.
params_to_tune()	Get grid for tuning hyperparameters.
predict(ts[, prediction_interval, ...])	Make predictions with using true values as autoregression context if possible (teacher forcing).
save(path)	Save the object.
set_params(**params)	Return new object instance with modified parameters.
to_dict()	Collect all information about etna object in dict.

Attributes

context_size

Context size of the model.