org.apache.commons.math3.distribution
Class MixtureMultivariateNormalDistribution
java.lang.Object
org.apache.commons.math3.distribution.AbstractMultivariateRealDistribution
org.apache.commons.math3.distribution.MixtureMultivariateRealDistribution<MultivariateNormalDistribution>
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.java 1459551 2013-03-21 22:17:44Z tn $
- See Also:
MixtureMultivariateRealDistribution
Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
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.
createComponents
private static List<Pair<Double,MultivariateNormalDistribution>> createComponents(double[] weights,
double[][] means,
double[][][] covariances)
- Parameters:
weights
- Weights of each component.means
- Mean vector for each component.covariances
- Covariance matrix for each component.
- Returns:
- the list of components.
Copyright (c) 2003-2013 Apache Software Foundation