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

Class MultivariateAutoCovarianceFunction

java.lang.Object

dev.nm.analysis.function.matrix.R2toMatrix

dev.nm.stat.timeseries.linear.multivariate.MultivariateAutoCovarianceFunction

All Implemented Interfaces:

Function<Vector,Matrix>, RntoMatrix

Direct Known Subclasses:

VARMAAutoCovariance

public abstract class MultivariateAutoCovarianceFunction
extends R2toMatrix

This is the auto-covariance function of a multi-dimensional time series {X_t}, \[ K(i, j) = E((X_i - \mu_i) \times (X_j - \mu_j)') \] For a stationary process, the auto-covariance depends only on the lag, |i - j|.

Nested Class Summary

Nested classes/interfaces inherited from interface dev.nm.analysis.function.Function

Function.EvaluationException

Constructor Summary

Constructors

Constructor	Description
MultivariateAutoCovarianceFunction()

Method Summary

Modifier and Type	Method	Description
Matrix	get(int i, int j)	Get the auto-covariance matrix for Xi and Xj.

Methods inherited from class dev.nm.analysis.function.matrix.R2toMatrix

dimensionOfDomain, dimensionOfRange, evaluate, evaluate

Methods inherited from class java.lang.Object

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

Constructor Details

MultivariateAutoCovarianceFunction

public MultivariateAutoCovarianceFunction()

Method Details

get

public Matrix get(int i,
 int j)

Get the auto-covariance matrix for X_i and X_j.

Parameters:

i - i > 0

j - j > 0

Returns:

the auto-covariance matrix indexed by [i, j]