Class MixtureMultivariateNormalDistribution
- java.lang.Object
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- org.apache.commons.math4.legacy.distribution.AbstractMultivariateRealDistribution
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- org.apache.commons.math4.legacy.distribution.MixtureMultivariateRealDistribution<MultivariateNormalDistribution>
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- org.apache.commons.math4.legacy.distribution.MixtureMultivariateNormalDistribution
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- 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
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Nested Class Summary
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Nested classes/interfaces inherited from interface org.apache.commons.math4.legacy.distribution.MultivariateRealDistribution
MultivariateRealDistribution.Sampler
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Constructor Summary
Constructors Constructor Description 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.
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Method Summary
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Methods inherited from class org.apache.commons.math4.legacy.distribution.MixtureMultivariateRealDistribution
createSampler, density, getComponents
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Methods inherited from class org.apache.commons.math4.legacy.distribution.AbstractMultivariateRealDistribution
getDimension, sample
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Constructor Detail
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MixtureMultivariateNormalDistribution
public MixtureMultivariateNormalDistribution(List<Pair<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.
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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.
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