Package org.apache.commons.math4.legacy.distribution

Class MixtureMultivariateNormalDistribution

java.lang.Object

org.apache.commons.math4.legacy.distribution.AbstractMultivariateRealDistribution

org.apache.commons.math4.legacy.distribution.MixtureMultivariateRealDistribution<MultivariateNormalDistribution>

org.apache.commons.math4.legacy.distribution.MixtureMultivariateNormalDistribution

All Implemented Interfaces:

MultivariateRealDistribution

public class MixtureMultivariateNormalDistribution
extends MixtureMultivariateRealDistribution<MultivariateNormalDistribution>

Multivariate normal mixture distribution. This class is mainly syntactic sugar.

Since:

3.2

See Also:

MixtureMultivariateRealDistribution

Nested Class Summary

Nested classes/interfaces inherited from interface org.apache.commons.math4.legacy.distribution.MultivariateRealDistribution

MultivariateRealDistribution.Sampler

Constructor Summary

Constructors

Constructor	Description
MixtureMultivariateNormalDistribution(double[] weights, double[][] means, double[][][] covariances)	Creates a multivariate normal mixture distribution.
MixtureMultivariateNormalDistribution(List<Pair<Double,MultivariateNormalDistribution>> components)	Creates a mixture model from a list of distributions and their associated weights.

Method Summary

Methods inherited from class org.apache.commons.math4.legacy.distribution.MixtureMultivariateRealDistribution

createSampler, density, getComponents

Methods inherited from class org.apache.commons.math4.legacy.distribution.AbstractMultivariateRealDistribution

getDimension, sample

Methods inherited from class java.lang.Object

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

Constructor Detail

MixtureMultivariateNormalDistribution

public MixtureMultivariateNormalDistribution(List<Pair<Double,MultivariateNormalDistribution>> components)
                                      throws NotPositiveException,
                                             DimensionMismatchException

Creates a mixture model from a list of distributions and their associated weights.

Parameters:

components - Distributions from which to sample.

Throws:

NotPositiveException - if any of the weights is negative.

DimensionMismatchException - if not all components have the same number of variables.

MixtureMultivariateNormalDistribution

public MixtureMultivariateNormalDistribution(double[] weights,
                                             double[][] means,
                                             double[][][] covariances)
                                      throws NotPositiveException,
                                             DimensionMismatchException

Creates a multivariate normal mixture distribution.

Parameters:

weights - Weights of each component.

means - Mean vector for each component.

covariances - Covariance matrix for each component.

Throws:

NotPositiveException - if any of the weights is negative.

DimensionMismatchException - if not all components have the same number of variables.