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Java example source code file (MixtureMultivariateNormalDistribution.java)
The MixtureMultivariateNormalDistribution.java Java example source code/* * Licensed to the Apache Software Foundation (ASF) under one or more * contributor license agreements. See the NOTICE file distributed with * this work for additional information regarding copyright ownership. * The ASF licenses this file to You under the Apache License, Version 2.0 * (the "License"); you may not use this file except in compliance with * the License. You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ package org.apache.commons.math3.distribution; import java.util.ArrayList; import java.util.List; import org.apache.commons.math3.exception.DimensionMismatchException; import org.apache.commons.math3.exception.NotPositiveException; import org.apache.commons.math3.random.RandomGenerator; import org.apache.commons.math3.util.Pair; /** * Multivariate normal mixture distribution. * This class is mainly syntactic sugar. * * @see MixtureMultivariateRealDistribution * @since 3.2 */ public class MixtureMultivariateNormalDistribution extends MixtureMultivariateRealDistribution<MultivariateNormalDistribution> { /** * Creates a multivariate normal mixture distribution. * <p> * <b>Note: this constructor will implicitly create an instance of * {@link org.apache.commons.math3.random.Well19937c Well19937c} as random * generator to be used for sampling only (see {@link #sample()} and * {@link #sample(int)}). In case no sampling is needed for the created * distribution, it is advised to pass {@code null} as random generator via * the appropriate constructors to avoid the additional initialisation * overhead. * * @param weights Weights of each component. * @param means Mean vector for each component. * @param covariances Covariance matrix for each component. */ public MixtureMultivariateNormalDistribution(double[] weights, double[][] means, double[][][] covariances) { super(createComponents(weights, means, covariances)); } /** * Creates a mixture model from a list of distributions and their * associated weights. * <p> * <b>Note: this constructor will implicitly create an instance of * {@link org.apache.commons.math3.random.Well19937c Well19937c} as random * generator to be used for sampling only (see {@link #sample()} and * {@link #sample(int)}). In case no sampling is needed for the created * distribution, it is advised to pass {@code null} as random generator via * the appropriate constructors to avoid the additional initialisation * overhead. * * @param components List of (weight, distribution) pairs from which to sample. */ public MixtureMultivariateNormalDistribution(List<Pair Other Java examples (source code examples)Here is a short list of links related to this Java MixtureMultivariateNormalDistribution.java source code file: |
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