@krzysztofsztompka/garch
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    Type Alias VolatilityForecastRequest

    The two whole questions a caller asks, as plain data in and out — so they can cross a worker boundary (structured clone) unchanged.

    type VolatilityForecastRequest = {
        dist?: Distribution;
        exogenous?: ArrayLike<number>;
        horizon: number;
        mean?: MeanModel;
        minTrain?: number;
        model?: GarchModel;
        returns: ArrayLike<number>;
        rivalsWithin?: number;
        step?: number;
        targetVariance?: boolean;
    }
    Index
    dist? exogenous? horizon mean? minTrain? model? returns rivalsWithin? step? targetVariance?
    dist?: Distribution
    exogenous?: ArrayLike<number>

    GARCH-X: x aligned with the returns (garch and gjr); see FitOptions.exogenous. Forecasts hold it at its last value.

    horizon: number
    mean?: MeanModel

    A fitted constant (default) or zero; see FitOptions.mean.

    minTrain?: number
    model?: GarchModel
    returns: ArrayLike<number>
    rivalsWithin?: number

    Also return the rival optima within this many log-likelihood units of the best.

    step?: number
    targetVariance?: boolean

    Variance targeting (garch and gjr); see FitOptions.targetVariance.

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