com.numericalmethod.suanshu.stats.timeseries.linear.multivariate.stationaryprocess.arima.arma
Class InnovationAlgorithm

java.lang.Object
  com.numericalmethod.suanshu.stats.timeseries.linear.multivariate.stationaryprocess.InnovationAlgorithmImpl
      com.numericalmethod.suanshu.stats.timeseries.linear.multivariate.stationaryprocess.arima.arma.InnovationAlgorithm

public class InnovationAlgorithm
extends InnovationAlgorithmImpl

This is an implementation, adapted for an ARMA process, of the innovation algorithm, which is an efficient way of obtaining a one step least square linear predictor.

See Also:

• "P. J. Brockwell and R. A. Davis, "Chapter 5.3. Recursive Prediction of an ARMA(p,q) Process," in Time Series: Theory and Methods, Springer, 2006."
• "P. J. Brockwell and R. A. Davis, "Eqs. 11.4.26, 11.4.27, 11.4.28, Chapter 11.4 Recursive Prediction of an ARMA(p,q) Process, Best Linear Predictors of Second Order Random Vectors," in Time Series: Theory and Methods, Springer, 2006."

Field Summary

Fields inherited from class com.numericalmethod.suanshu.stats.timeseries.linear.multivariate.stationaryprocess.InnovationAlgorithmImpl

XtHat

Constructor Summary

InnovationAlgorithm(MultiVariateTimeSeries Xt, ArmaModel model)
Construct an instance of InnovationAlgorithm for a multivariate ARMA time series.

Method Summary

Methods inherited from class com.numericalmethod.suanshu.stats.timeseries.linear.multivariate.stationaryprocess.InnovationAlgorithmImpl

covariance, getTheta, run, XtHat, XtHat

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

InnovationAlgorithm

public InnovationAlgorithm(MultiVariateTimeSeries Xt,
                           ArmaModel model)

Construct an instance of InnovationAlgorithm for a multivariate ARMA time series.

Parameters:

Xt - an m-dimensional time series, length t

model - the ARMA model