StatsForecastARIMAModel

class StatsForecastARIMAModel(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.mixins.PerSegmentModelMixin, etna.models.mixins.PredictionIntervalContextIgnorantModelMixin, etna.models.base.PredictionIntervalContextIgnorantAbstractModel

Class for holding statsforecast.models.ARIMA.

Documentation for the underlying model.

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(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 default 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.
params_to_tune() → Dict[str, etna.distributions.distributions.BaseDistribution][source]

Get default grid for tuning hyperparameters.

This grid tunes parameters: order.0, order.1, order.2. If self.season_length is greater than one, then it also tunes parameters: seasonal_order.0, seasonal_order.1, seasonal_order.2. Other parameters are expected to be set by the user.

Returns

Grid to tune.

Return type

Dict[str, etna.distributions.distributions.BaseDistribution]