MixtureMultivariateNormalDistribution (nosqlbench)

java.lang.Object

org.apache.commons.math4.distribution.AbstractMultivariateRealDistribution

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

org.apache.commons.math4.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.distribution.MultivariateRealDistribution
MultivariateRealDistribution.Sampler

Constructor Summary

Constructors
Constructor	Description
`MixtureMultivariateNormalDistribution(double[] weights, double[][] means, double[][][] covariances)`	Creates a multivariate normal mixture distribution.
`MixtureMultivariateNormalDistribution(java.util.List<Pair<java.lang.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.distribution.MixtureMultivariateRealDistribution
createSampler, density, getComponents

Methods inherited from class org.apache.commons.math4.distribution.AbstractMultivariateRealDistribution
getDimension, sample

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Details
- MixtureMultivariateNormalDistribution
  
  public MixtureMultivariateNormalDistribution(java.util.List<Pair<java.lang.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.