org.apache.commons.math3.distribution

Class MixtureMultivariateRealDistribution<T extends MultivariateRealDistribution>

java.lang.Object

org.apache.commons.math3.distribution.AbstractMultivariateRealDistribution

org.apache.commons.math3.distribution.MixtureMultivariateRealDistribution<T>

Type Parameters:

T - Type of the mixture components.

All Implemented Interfaces:

MultivariateRealDistribution

Direct Known Subclasses:

MixtureMultivariateNormalDistribution

public class MixtureMultivariateRealDistribution<T extends MultivariateRealDistribution>
extends AbstractMultivariateRealDistribution

Class for representing mixture model distributions.

Since:

3.1

Field Summary

Fields

Modifier and Type	Field and Description
private java.util.List<T>	distribution Mixture components.
private double[]	weight Normalized weight of each mixture component.

Fields inherited from class org.apache.commons.math3.distribution.AbstractMultivariateRealDistribution

random

Constructor Summary

Constructors

Constructor and Description
MixtureMultivariateRealDistribution(java.util.List<Pair<java.lang.Double,T>> components) Creates a mixture model from a list of distributions and their associated weights.
MixtureMultivariateRealDistribution(RandomGenerator rng, java.util.List<Pair<java.lang.Double,T>> components) Creates a mixture model from a list of distributions and their associated weights.

Method Summary

Methods

Modifier and Type	Method and Description
double	density(double[] values) Returns the probability density function (PDF) of this distribution evaluated at the specified point x.
java.util.List<Pair<java.lang.Double,T>>	getComponents() Gets the distributions that make up the mixture model.
void	reseedRandomGenerator(long seed) Reseeds the random generator used to generate samples.
double[]	sample() Generates a random value vector sampled from this distribution.

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

Field Detail

weight

private final double[] weight

Normalized weight of each mixture component.

distribution

private final java.util.List<T extends MultivariateRealDistribution> distribution

Mixture components.

Constructor Detail

MixtureMultivariateRealDistribution

public MixtureMultivariateRealDistribution(java.util.List<Pair<java.lang.Double,T>> components)

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

Note: this constructor will implicitly create an instance of Well19937c as random generator to be used for sampling only (see sample() and AbstractMultivariateRealDistribution.sample(int)). In case no sampling is needed for the created distribution, it is advised to pass null as random generator via the appropriate constructors to avoid the additional initialisation overhead.

Parameters:

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

MixtureMultivariateRealDistribution

public MixtureMultivariateRealDistribution(RandomGenerator rng,
                                   java.util.List<Pair<java.lang.Double,T>> components)

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.

Method Detail

density

public double density(double[] values)

Returns the probability density function (PDF) of this distribution evaluated at the specified point x. In general, the PDF is the derivative of the cumulative distribution function. If the derivative does not exist at x, then an appropriate replacement should be returned, e.g. Double.POSITIVE_INFINITY, Double.NaN, or the limit inferior or limit superior of the difference quotient.

Parameters:

values - Point at which the PDF is evaluated.

Returns:

the value of the probability density function at point x.

sample

public double[] sample()

Generates a random value vector sampled from this distribution.

Specified by:

sample in interface MultivariateRealDistribution

Specified by:

sample in class AbstractMultivariateRealDistribution

Returns:

a random value vector.

reseedRandomGenerator

public void reseedRandomGenerator(long seed)

Reseeds the random generator used to generate samples.

Specified by:

reseedRandomGenerator in interface MultivariateRealDistribution

Overrides:

reseedRandomGenerator in class AbstractMultivariateRealDistribution

Parameters:

seed - Seed with which to initialize the random number generator.

getComponents

public java.util.List<Pair<java.lang.Double,T>> getComponents()

Gets the distributions that make up the mixture model.

Returns:

the component distributions and associated weights.