Class GARCH

All Implemented Interfaces:
ScedasticityModel

public final class GARCH extends AbstractScedasticity
  • Field Details

    • myARCH

      private final ARCH myARCH
    • myVariances

      private final double[] myVariances
    • myWeights

      private final double[] myWeights
  • Constructor Details

    • GARCH

      public GARCH(int p, int q)
  • Method Details

    • estimate

      public static GARCH estimate(Access1D<?> series, int p, int q)
      Parameter estimation using heuristics (not max likelihood).
      Parameters:
      series - Series to adapt to
      p - Number of lagged variance values
      q - Number of lagged squared error terms
      Returns:
      Ready to use GARCH model
    • newInstance

      public static GARCH newInstance(int p, int q)
      See Also:
    • newInstance

      public static GARCH newInstance(int p, int q, double mean, double variance)
      Will create an instance configured with default parameters. What these are may change in the future. You're better of estimating suitable paramaters for your use case and then set base(double), errorWeights(double...) and varianceWeights(double...).
    • base

      public GARCH base(double base)
    • errorWeights

      public GARCH errorWeights(double... lagged)
    • getMean

      public double getMean()
    • getVariance

      public double getVariance()
    • initialise

      public void initialise(double mean, double variance)
    • update

      public void update(double value)
    • varianceWeights

      public GARCH varianceWeights(double... lagged)