java.lang.Object
dev.nm.stat.timeseries.linear.multivariate.arima.VARIMAXModel
dev.nm.stat.timeseries.linear.multivariate.arima.VARIMAModel
Direct Known Subclasses:
VARMAModel

public class VARIMAModel extends VARIMAXModel
An ARIMA(p, d, q) process, Yt, is such that \[ X_t = (1 - L)^d Y_t \] where L is the lag operator, d the order of difference, Xt an ARMA(p, q) process, for which \[ X_t = \mu + \Sigma \phi_i X_{t-i} + \Sigma \theta_j \epsilon_{t-j} + \epsilon_t, \] Xt, μ and εt are n-dimensional vectors. The (n * n) matrices \({\phi_i}\) and \({\theta_j}\) are the AR and MA coefficients respectively.
See Also:
  • Constructor Details

    • VARIMAModel

      public VARIMAModel(Vector mu, Matrix[] phi, int d, Matrix[] theta, Matrix sigma)
      Construct a multivariate ARIMA model.
      Parameters:
      mu - the intercept (constant) vector
      phi - the AR coefficients (excluding the initial 1); null if no AR coefficient
      d - the order of integration
      theta - the MA coefficients (excluding the initial 1); null if no MA coefficient
      sigma - the white noise covariance matrix
    • VARIMAModel

      public VARIMAModel(Vector mu, Matrix[] phi, int d, Matrix[] theta)
      Construct a multivariate ARIMA model with unit variance.
      Parameters:
      mu - the intercept (constant) vector
      phi - the AR coefficients (excluding the initial 1); null if no AR coefficient
      d - the order of integration
      theta - the MA coefficients (excluding the initial 1); null if no MA coefficient
    • VARIMAModel

      public VARIMAModel(Matrix[] phi, int d, Matrix[] theta, Matrix sigma)
      Construct a multivariate ARIMA model with zero-intercept (mu).
      Parameters:
      phi - the AR coefficients (excluding the initial 1); null if no AR coefficient
      d - the order of integration
      theta - the MA coefficients (excluding the initial 1); null if no MA coefficient
      sigma - the white noise covariance matrix
    • VARIMAModel

      public VARIMAModel(Matrix[] phi, int d, Matrix[] theta)
      Construct a multivariate ARIMA model with unit variance and zero-intercept (mu).
      Parameters:
      phi - the AR coefficients (excluding the initial 1); null if no AR coefficient
      d - the order of integration
      theta - the MA coefficients (excluding the initial 1); null if no MA coefficient
    • VARIMAModel

      public VARIMAModel(ARIMAModel model)
      Construct a multivariate model from a univariate ARIMA model.
      Parameters:
      model - a univariate ARIMA model
    • VARIMAModel

      public VARIMAModel(VARIMAModel that)
      Copy constructor.
      Parameters:
      that - a multivariate ARIMA model
  • Method Details

    • getVARMA

      public VARMAModel getVARMA()
      Get the ARMA part of this ARIMA model, essentially ignoring the differencing.
      Returns:
      the ARMA part