gluonts.ext.statsforecast module#
- class gluonts.ext.statsforecast.ADIDAPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
StatsForecastPredictorA predictor wrapping the
ADIDAmodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
ADIDA
- class gluonts.ext.statsforecast.AutoARIMAPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
StatsForecastPredictorA predictor wrapping the
AutoARIMAmodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
AutoARIMA
- class gluonts.ext.statsforecast.AutoCESPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
StatsForecastPredictorA predictor wrapping the
AutoCESmodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
AutoCES
- class gluonts.ext.statsforecast.AutoETSPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
StatsForecastPredictorA predictor wrapping the
AutoETSmodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
AutoETS
- class gluonts.ext.statsforecast.AutoThetaPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
StatsForecastPredictorA predictor wrapping the
AutoThetamodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
AutoTheta
- class gluonts.ext.statsforecast.CrostonClassicPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
StatsForecastPredictorA predictor wrapping the
CrostonClassicmodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
CrostonClassic
- class gluonts.ext.statsforecast.CrostonOptimizedPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
StatsForecastPredictorA predictor wrapping the
CrostonOptimizedmodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
CrostonOptimized
- class gluonts.ext.statsforecast.CrostonSBAPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
StatsForecastPredictorA predictor wrapping the
CrostonSBAmodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
CrostonSBA
- class gluonts.ext.statsforecast.DynamicOptimizedThetaPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
StatsForecastPredictorA predictor wrapping the
DynamicOptimizedThetamodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
DynamicOptimizedTheta
- class gluonts.ext.statsforecast.DynamicThetaPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
StatsForecastPredictorA predictor wrapping the
DynamicThetamodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
DynamicTheta
- class gluonts.ext.statsforecast.HistoricAveragePredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
StatsForecastPredictorA predictor wrapping the
HistoricAveragemodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
HistoricAverage
- class gluonts.ext.statsforecast.HoltPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
StatsForecastPredictorA predictor wrapping the
Holtmodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
Holt
- class gluonts.ext.statsforecast.HoltWintersPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
StatsForecastPredictorA predictor wrapping the
HoltWintersmodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
HoltWinters
- class gluonts.ext.statsforecast.IMAPAPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
StatsForecastPredictorA predictor wrapping the
IMAPAmodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
IMAPA
- class gluonts.ext.statsforecast.MSTLPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
StatsForecastPredictorA predictor wrapping the
MSTLmodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
MSTL
- class gluonts.ext.statsforecast.ModelConfig(quantile_levels: Optional[List[float]] = 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:
StatsForecastPredictorA predictor wrapping the
Naivemodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
Naive
- class gluonts.ext.statsforecast.OptimizedThetaPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
StatsForecastPredictorA predictor wrapping the
OptimizedThetamodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
OptimizedTheta
- class gluonts.ext.statsforecast.RandomWalkWithDriftPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
StatsForecastPredictorA predictor wrapping the
RandomWalkWithDriftmodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
RandomWalkWithDrift
- class gluonts.ext.statsforecast.SeasonalExponentialSmoothingOptimizedPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
StatsForecastPredictorA predictor wrapping the
SeasonalExponentialSmoothingOptimizedmodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
SeasonalExponentialSmoothingOptimized
- class gluonts.ext.statsforecast.SeasonalExponentialSmoothingPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
StatsForecastPredictorA predictor wrapping the
SeasonalExponentialSmoothingmodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
SeasonalExponentialSmoothing
- class gluonts.ext.statsforecast.SeasonalNaivePredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
StatsForecastPredictorA predictor wrapping the
SeasonalNaivemodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
SeasonalNaive
- class gluonts.ext.statsforecast.SeasonalWindowAveragePredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
StatsForecastPredictorA predictor wrapping the
SeasonalWindowAveragemodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
SeasonalWindowAverage
- class gluonts.ext.statsforecast.SimpleExponentialSmoothingOptimizedPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
StatsForecastPredictorA predictor wrapping the
SimpleExponentialSmoothingOptimizedmodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
SimpleExponentialSmoothingOptimized
- class gluonts.ext.statsforecast.SimpleExponentialSmoothingPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
StatsForecastPredictorA predictor wrapping the
SimpleExponentialSmoothingmodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
SimpleExponentialSmoothing
- class gluonts.ext.statsforecast.StatsForecastPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
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]) QuantileForecast[source]#
- class gluonts.ext.statsforecast.TSBPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
StatsForecastPredictorA predictor wrapping the
TSBmodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
TSB
- class gluonts.ext.statsforecast.ThetaPredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
StatsForecastPredictorA predictor wrapping the
Thetamodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
Theta
- class gluonts.ext.statsforecast.WindowAveragePredictor(prediction_length: int, quantile_levels: Optional[List[float]] = None, **model_params)[source]#
Bases:
StatsForecastPredictorA predictor wrapping the
WindowAveragemodel from statsforecast.See
StatsForecastPredictorfor the list of arguments.- ModelType#
alias of
WindowAverage