org.apache.commons.math3.distribution
Class MixtureMultivariateNormalDistribution

java.lang.Object
  extended by org.apache.commons.math3.distribution.AbstractMultivariateRealDistribution
      extended by org.apache.commons.math3.distribution.MixtureMultivariateRealDistribution<MultivariateNormalDistribution>
          extended by org.apache.commons.math3.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
Version:
$Id: MixtureMultivariateNormalDistribution.html 860130 2013-04-27 21:11:39Z luc $
See Also:
MixtureMultivariateRealDistribution

Field Summary
 
Fields inherited from class org.apache.commons.math3.distribution.AbstractMultivariateRealDistribution
random
 
Constructor Summary
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.
MixtureMultivariateNormalDistribution(RandomGenerator rng, 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.math3.distribution.MixtureMultivariateRealDistribution
density, getComponents, reseedRandomGenerator, sample
 
Methods inherited from class org.apache.commons.math3.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(double[] weights,
                                             double[][] means,
                                             double[][][] covariances)
Creates a multivariate normal mixture distribution.

Parameters:
weights - Weights of each component.
means - Mean vector for each component.
covariances - Covariance matrix for each component.

MixtureMultivariateNormalDistribution

public MixtureMultivariateNormalDistribution(List<Pair<Double,MultivariateNormalDistribution>> components)
Creates a mixture model from a list of distributions and their associated weights.

Parameters:
components - List of (weight, distribution) pairs from which to sample.

MixtureMultivariateNormalDistribution

public MixtureMultivariateNormalDistribution(RandomGenerator rng,
                                             List<Pair<Double,MultivariateNormalDistribution>> components)
                                      throws NotPositiveException,
                                             DimensionMismatchException
Creates a mixture model from a list of distributions and their associated weights.

Parameters:
rng - Random number generator.
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.


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