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

java.lang.Object
  com.numericalmethod.suanshu.stats.timeseries.linear.multivariate.stationaryprocess.arima.ArimaxModel
      com.numericalmethod.suanshu.stats.timeseries.linear.multivariate.stationaryprocess.arima.ArimaModel
          com.numericalmethod.suanshu.stats.timeseries.linear.multivariate.stationaryprocess.arima.arma.ArmaModel
              com.numericalmethod.suanshu.stats.timeseries.linear.multivariate.stationaryprocess.arima.arma.MaModel

public class MaModel
extends ArmaModel

This class represents a multivariate MA model.

Field Summary

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

mu, phi, psi, sigma, theta

Constructor Summary

MaModel(MaModel that)
Copy constructor.

MaModel(MaModel model)
Cast a univariate MA model to a multivariate model.

MaModel(Matrix[] theta)
Construct a zero-mean multivariate MA model with unit variance.

MaModel(Matrix[] theta, Matrix sigma)
Construct a zero-mean multivariate MA model.

MaModel(Vector mu, Matrix[] theta)
Construct a multivariate MA model with unit variance.

MaModel(Vector mu, Matrix[] theta, Matrix sigma)
Construct a multivariate MA model.

Method Summary

Methods inherited from class com.numericalmethod.suanshu.stats.timeseries.linear.multivariate.stationaryprocess.arima.arma.ArmaModel

armaMean, armaMeanNoIntercept

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

getArma

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

AR, AR, d, dimension, getArmax, MA, MA, maxPQ, mu, p, psi, q, sigma

Methods inherited from class java.lang.Object

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

Constructor Detail

MaModel

public MaModel(Vector mu,
               Matrix[] theta,
               Matrix sigma)

Construct a multivariate MA model.

Parameters:

mu - the intercept (constant) vector

theta - the MA coefficients (excluding the initial 1); null if no MA coefficients

sigma - the covariance matrix of white noise

MaModel

public MaModel(Vector mu,
               Matrix[] theta)

Construct a multivariate MA model with unit variance.

Parameters:

mu - the intercept (constant) vector

theta - the MA coefficients (excluding the initial 1); null if no MA coefficients

MaModel

public MaModel(Matrix[] theta,
               Matrix sigma)

Construct a zero-mean multivariate MA model.

Parameters:

theta - the MA coefficients (excluding the initial 1); null if no MA coefficients

sigma - the covariance matrix of white noise

MaModel

public MaModel(Matrix[] theta)

Construct a zero-mean multivariate MA model with unit variance.

Parameters:

theta - the MA coefficients (excluding the initial 1); null if no MA coefficients

MaModel

public MaModel(MaModel that)

Copy constructor.

Parameters:

that - a multivariate MA model

MaModel

public MaModel(MaModel model)

Cast a univariate MA model to a multivariate model.

Parameters:

model - a univariate MA model