CrostonForecaster

yohou_nixtla.stats.CrostonForecaster

Bases: BaseStatsForecaster

Croston's method forecaster via statsforecast.

Designed for intermittent demand forecasting.

Parameters

Name	Type	Description	Default
freq	str or None	Frequency string. Auto-inferred from data if None.	None
feature_transformer	BaseTransformer or None	Transformer applied to exogenous features before fitting/predicting.	None
target_transformer	BaseTransformer or None	Transformer applied to the target before fitting. Inverse-transformed after predicting to return forecasts in the original scale.	None
target_as_feature	('transformed', 'raw')	Whether to include target values as additional features.	"transformed"
**params	dict	Additional parameters forwarded to statsforecast.models.CrostonClassic.	{}

Attributes

Name	Type	Description
nixtla_forecaster_	StatsForecast	The fitted Nixtla orchestrator.
instance_	CrostonClassic	The constructed Croston model instance.

See Also

NaiveForecaster : Non-seasonal naive baseline. SeasonalNaiveForecaster : Seasonal naive baseline.

Examples

>>> from yohou_nixtla.stats import CrostonForecaster
>>> forecaster = CrostonForecaster()
>>> forecaster
CrostonForecaster(...)

Source Code

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class CrostonForecaster(BaseStatsForecaster):
    """Croston's method forecaster via statsforecast.

    Designed for intermittent demand forecasting.

    Parameters
    ----------
    freq : str or None, default=None
        Frequency string. Auto-inferred from data if None.
    feature_transformer : BaseTransformer or None, default=None
        Transformer applied to exogenous features before fitting/predicting.
    target_transformer : BaseTransformer or None, default=None
        Transformer applied to the target before fitting. Inverse-transformed
        after predicting to return forecasts in the original scale.
    target_as_feature : {"transformed", "raw"} or None, default=None
        Whether to include target values as additional features.
    **params : dict
        Additional parameters forwarded to ``statsforecast.models.CrostonClassic``.

    Attributes
    ----------
    nixtla_forecaster_ : StatsForecast
        The fitted Nixtla orchestrator.
    instance_ : CrostonClassic
        The constructed Croston model instance.

    See Also
    --------
    NaiveForecaster : Non-seasonal naive baseline.
    SeasonalNaiveForecaster : Seasonal naive baseline.

    Examples
    --------
    >>> from yohou_nixtla.stats import CrostonForecaster
    >>> forecaster = CrostonForecaster()
    >>> forecaster  # doctest: +ELLIPSIS
    CrostonForecaster(...)

    """

    _estimator_default_class = CrostonClassic