Class VARMAAutoCorrelation

  • All Implemented Interfaces:
    Function<Vector,​Matrix>, RntoMatrix

    public class VARMAAutoCorrelation
    extends MultivariateAutoCorrelationFunction
    Compute the Auto-Correlation Function (ACF) for a vector AutoRegressive Moving Average (ARMA) model, assuming that EXt = 0.

    This implementation solves the Yule-Walker equation.

    The R equivalent functions are ARMAacf and TacvfAR in package FitAR.

    • Constructor Detail

      • VARMAAutoCorrelation

        public VARMAAutoCorrelation​(VARMAModel model,
                                    int nLags)
        Compute the auto-correlation function for a vector ARMA model.
        Parameters:
        model - an ARIMA model
        nLags - the number of lags
    • Method Detail

      • evaluate

        public Matrix evaluate​(double i,
                               double j)
        Description copied from class: R2toMatrix
        Evaluate f(x1, x2) = A.
        Specified by:
        evaluate in class R2toMatrix
        Parameters:
        i - x1
        j - x2
        Returns:
        f(x1, x2)
      • evaluate

        public Matrix evaluate​(double i)
        Get the i-th auto-correlation matrix.
        Parameters:
        i - the lag order
        Returns:
        the i-th auto-correlation matrix