_ARIMAAdapter

class _ARIMAAdapter(order: Tuple[int, int, int] = (0, 0, 0), season_length: int = 1, seasonal_order: Tuple[int, int, int] = (0, 0, 0), **kwargs)[source]

Bases: etna.models.statsforecast._StatsForecastBaseAdapter

Adapter for statsforecast.models.ARIMA.

Init model with given params.

Parameters

  • order (Tuple[int, int, int]) – A specification of the non-seasonal part of the ARIMA model: the three components (p, d, q) are the AR order, the degree of differencing, and the MA order.

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

  • seasonal_order (Tuple[int, int, int]) – A specification of the seasonal part of the ARIMA model. (P, D, Q) for the AR order, the degree of differencing, the MA order.

  • **kwargs – Additional parameters for statsforecast.models.ARIMA.

Inherited-members

Methods

fit(df, regressors)

Fit statsforecast adapter.

forecast(df[, prediction_interval, quantiles])

Compute predictions on future data from a statsforecast model.

forecast_components(df)

Estimate forecast components.

get_model()

Get statsforecast model that is used inside etna class.

predict(df[, prediction_interval, quantiles])

Compute in-sample predictions from a statsforecast model.

predict_components(df)

Estimate prediction components.