Package dev.nm.stat.timeseries.linear.multivariate.stationaryprocess.arma

Class VMAModel

java.lang.Object

dev.nm.stat.timeseries.linear.multivariate.arima.VARIMAXModel

dev.nm.stat.timeseries.linear.multivariate.arima.VARIMAModel

dev.nm.stat.timeseries.linear.multivariate.stationaryprocess.arma.VARMAModel

dev.nm.stat.timeseries.linear.multivariate.stationaryprocess.arma.VMAModel

public class VMAModel
extends VARMAModel

This class represents a multivariate MA model.

See Also:

Wikipedia: Moving average model

Constructor Summary

Constructors

Constructor	Description
VMAModel(Matrix[] theta)	Construct a multivariate MA model with unit variance and zero-mean.
VMAModel(Matrix[] theta, Matrix sigma)	Construct a multivariate MA model with zero-mean.
VMAModel(Vector mu, Matrix[] theta)	Construct a multivariate MA model with unit variance.
VMAModel(Vector mu, Matrix[] theta, Matrix sigma)	Construct a multivariate MA model.
VMAModel(VMAModel that)	Copy constructor.
VMAModel(MAModel model)	Construct a multivariate MA model from a univariate MA model.

Method Summary

Methods inherited from class dev.nm.stat.timeseries.linear.multivariate.stationaryprocess.arma.VARMAModel

conditionalMean, getDemeanedModel, unconditionalMean

Methods inherited from class dev.nm.stat.timeseries.linear.multivariate.arima.VARIMAModel

getVARMA

Methods inherited from class dev.nm.stat.timeseries.linear.multivariate.arima.VARIMAXModel

AR, d, dimension, getVARMAX, MA, maxPQ, mu, p, phi, psi, q, sigma, theta

Methods inherited from class java.lang.Object

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

Constructor Detail

VMAModel

public VMAModel(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 coefficient

sigma - the white noise covariance matrix

VMAModel

public VMAModel(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 coefficient

VMAModel

public VMAModel(Matrix[] theta,
                Matrix sigma)

Construct a multivariate MA model with zero-mean.

Parameters:

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

sigma - the white noise covariance matrix

VMAModel

public VMAModel(Matrix[] theta)

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

Parameters:

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

VMAModel

public VMAModel(MAModel model)

Construct a multivariate MA model from a univariate MA model.

Parameters:

model - a univariate MA model

VMAModel

public VMAModel(VMAModel that)

Copy constructor.

Parameters:

that - a multivariate MA model