gluonts.ext.statsforecast module#
- class gluonts.ext.statsforecast.ADIDAPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
gluonts.ext.statsforecast.StatsForecastPredictorA predictor wrapping the
ADIDAmodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
statsforecast.models.ADIDA
- class gluonts.ext.statsforecast.AutoARIMAPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
gluonts.ext.statsforecast.StatsForecastPredictorA predictor wrapping the
AutoARIMAmodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
statsforecast.models.AutoARIMA
- class gluonts.ext.statsforecast.AutoCESPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
gluonts.ext.statsforecast.StatsForecastPredictorA predictor wrapping the
AutoCESmodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
statsforecast.models.AutoCES
- class gluonts.ext.statsforecast.AutoETSPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
gluonts.ext.statsforecast.StatsForecastPredictorA predictor wrapping the
AutoETSmodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
statsforecast.models.AutoETS
- class gluonts.ext.statsforecast.AutoThetaPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
gluonts.ext.statsforecast.StatsForecastPredictorA predictor wrapping the
AutoThetamodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
statsforecast.models.AutoTheta
- class gluonts.ext.statsforecast.CrostonClassicPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
gluonts.ext.statsforecast.StatsForecastPredictorA predictor wrapping the
CrostonClassicmodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
statsforecast.models.CrostonClassic
- class gluonts.ext.statsforecast.CrostonOptimizedPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
gluonts.ext.statsforecast.StatsForecastPredictorA predictor wrapping the
CrostonOptimizedmodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
statsforecast.models.CrostonOptimized
- class gluonts.ext.statsforecast.CrostonSBAPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
gluonts.ext.statsforecast.StatsForecastPredictorA predictor wrapping the
CrostonSBAmodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
statsforecast.models.CrostonSBA
- class gluonts.ext.statsforecast.DynamicOptimizedThetaPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
gluonts.ext.statsforecast.StatsForecastPredictorA predictor wrapping the
DynamicOptimizedThetamodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
statsforecast.models.DynamicOptimizedTheta
- class gluonts.ext.statsforecast.DynamicThetaPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
gluonts.ext.statsforecast.StatsForecastPredictorA predictor wrapping the
DynamicThetamodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
statsforecast.models.DynamicTheta
- class gluonts.ext.statsforecast.HistoricAveragePredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
gluonts.ext.statsforecast.StatsForecastPredictorA predictor wrapping the
HistoricAveragemodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
statsforecast.models.HistoricAverage
- class gluonts.ext.statsforecast.HoltPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
gluonts.ext.statsforecast.StatsForecastPredictorA predictor wrapping the
Holtmodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
statsforecast.models.Holt
- class gluonts.ext.statsforecast.HoltWintersPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
gluonts.ext.statsforecast.StatsForecastPredictorA predictor wrapping the
HoltWintersmodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
statsforecast.models.HoltWinters
- class gluonts.ext.statsforecast.IMAPAPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
gluonts.ext.statsforecast.StatsForecastPredictorA predictor wrapping the
IMAPAmodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
statsforecast.models.IMAPA
- class gluonts.ext.statsforecast.MSTLPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
gluonts.ext.statsforecast.StatsForecastPredictorA predictor wrapping the
MSTLmodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
statsforecast.models.MSTL
- class gluonts.ext.statsforecast.ModelConfig(quantile_levels: Union[List[float], NoneType] = None)[source]#
Bases:
object- forecast_keys: List[str]#
- intervals: Optional[List[int]]#
- quantile_levels: Optional[List[float]] = None#
- statsforecast_keys: List[str]#
- class gluonts.ext.statsforecast.NaivePredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
gluonts.ext.statsforecast.StatsForecastPredictorA predictor wrapping the
Naivemodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
statsforecast.models.Naive
- class gluonts.ext.statsforecast.OptimizedThetaPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
gluonts.ext.statsforecast.StatsForecastPredictorA predictor wrapping the
OptimizedThetamodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
statsforecast.models.OptimizedTheta
- class gluonts.ext.statsforecast.RandomWalkWithDriftPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
gluonts.ext.statsforecast.StatsForecastPredictorA predictor wrapping the
RandomWalkWithDriftmodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
statsforecast.models.RandomWalkWithDrift
- class gluonts.ext.statsforecast.SeasonalExponentialSmoothingOptimizedPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
gluonts.ext.statsforecast.StatsForecastPredictorA predictor wrapping the
SeasonalExponentialSmoothingOptimizedmodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
statsforecast.models.SeasonalExponentialSmoothingOptimized
- class gluonts.ext.statsforecast.SeasonalExponentialSmoothingPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
gluonts.ext.statsforecast.StatsForecastPredictorA predictor wrapping the
SeasonalExponentialSmoothingmodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
statsforecast.models.SeasonalExponentialSmoothing
- class gluonts.ext.statsforecast.SeasonalNaivePredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
gluonts.ext.statsforecast.StatsForecastPredictorA predictor wrapping the
SeasonalNaivemodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
statsforecast.models.SeasonalNaive
- class gluonts.ext.statsforecast.SeasonalWindowAveragePredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
gluonts.ext.statsforecast.StatsForecastPredictorA predictor wrapping the
SeasonalWindowAveragemodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
statsforecast.models.SeasonalWindowAverage
- class gluonts.ext.statsforecast.SimpleExponentialSmoothingOptimizedPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
gluonts.ext.statsforecast.StatsForecastPredictorA predictor wrapping the
SimpleExponentialSmoothingOptimizedmodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
statsforecast.models.SimpleExponentialSmoothingOptimized
- class gluonts.ext.statsforecast.SimpleExponentialSmoothingPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
gluonts.ext.statsforecast.StatsForecastPredictorA predictor wrapping the
SimpleExponentialSmoothingmodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
statsforecast.models.SimpleExponentialSmoothing
- class gluonts.ext.statsforecast.StatsForecastPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
gluonts.model.predictor.RepresentablePredictorA predictor type that wraps models from the statsforecast package.
This class is used via subclassing and setting the
ModelTypeclass attribute to specify thestatsforecastmodel type to use.- Parameters
prediction_length – Prediction length for the model to use.
quantile_levels – Optional list of quantile levels that we want predictions for. Note: this is only supported by specific types of models, such as
AutoARIMA. By default this isNone, giving only the mean prediction.**model_params – Keyword arguments to be passed to the model type for construction. The specific arguments accepted or required depend on the
ModelType; please refer to the documentation ofstatsforecastfor details.
- ModelType: Type#
- predict_item(entry: Dict[str, Any]) gluonts.model.forecast.QuantileForecast[source]#
- class gluonts.ext.statsforecast.TSBPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
gluonts.ext.statsforecast.StatsForecastPredictorA predictor wrapping the
TSBmodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
statsforecast.models.TSB
- class gluonts.ext.statsforecast.ThetaPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
gluonts.ext.statsforecast.StatsForecastPredictorA predictor wrapping the
Thetamodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
statsforecast.models.Theta
- class gluonts.ext.statsforecast.WindowAveragePredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
gluonts.ext.statsforecast.StatsForecastPredictorA predictor wrapping the
WindowAveragemodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
statsforecast.models.WindowAverage