@krzysztofsztompka/garch
    Preparing search index...

    Type Alias WeightedForecastRequest

    weightedForecast's question: the returns, the horizon, the windows and the models to weigh.

    type WeightedForecastRequest = {
        burnIn?: number;
        exogenous?: ArrayLike<number>;
        horizon: number;
        mean?: MeanModel;
        minTrain?: number;
        models?: readonly ModelSpec[];
        returns: ArrayLike<number>;
        step?: number;
        targetVariance?: boolean;
    }
    Index
    burnIn? exogenous? horizon mean? minTrain? models? returns step? targetVariance?
    burnIn?: number
    exogenous?: ArrayLike<number>

    GARCH-X's x for every garch and gjr model; an egarch one is fitted without it.

    horizon: number
    mean?: MeanModel

    Every model's mean: a fitted constant (default) or zero.

    minTrain?: number
    models?: readonly ModelSpec[]
    returns: ArrayLike<number>
    step?: number
    targetVariance?: boolean

    Variance targeting for every garch and gjr model; an egarch one is fitted with ω free.

    Settings
    Member Visibility

    On This Page
    Properties