public class MixtureMultivariateNormalDistribution extends MixtureMultivariateRealDistribution<MultivariateNormalDistribution>
MixtureMultivariateRealDistributionrandom| Constructor and Description |
|---|
MixtureMultivariateNormalDistribution(double[] weights,
double[][] means,
double[][][] covariances)
Creates a multivariate normal mixture distribution.
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MixtureMultivariateNormalDistribution(List<Pair<Double,MultivariateNormalDistribution>> components)
Creates a mixture model from a list of distributions and their
associated weights.
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MixtureMultivariateNormalDistribution(RandomGenerator rng,
List<Pair<Double,MultivariateNormalDistribution>> components)
Creates a mixture model from a list of distributions and their
associated weights.
|
density, getComponents, reseedRandomGenerator, samplegetDimension, samplepublic MixtureMultivariateNormalDistribution(double[] weights,
double[][] means,
double[][][] covariances)
Note: this constructor will implicitly create an instance of
Well19937c as random
generator to be used for sampling only (see MixtureMultivariateRealDistribution.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.
weights - Weights of each component.means - Mean vector for each component.covariances - Covariance matrix for each component.public MixtureMultivariateNormalDistribution(List<Pair<Double,MultivariateNormalDistribution>> components)
Note: this constructor will implicitly create an instance of
Well19937c as random
generator to be used for sampling only (see MixtureMultivariateRealDistribution.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.
components - List of (weight, distribution) pairs from which to sample.public MixtureMultivariateNormalDistribution(RandomGenerator rng, List<Pair<Double,MultivariateNormalDistribution>> components) throws NotPositiveException, DimensionMismatchException
rng - Random number generator.components - Distributions from which to sample.NotPositiveException - if any of the weights is negative.DimensionMismatchException - if not all components have the same
number of variables.Copyright © 2003–2016 The Apache Software Foundation. All rights reserved.