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/*
 * 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.
 */

/*
 * This is not the original file distributed by the Apache Software Foundation
 * It has been modified by the Hipparchus project
 */
package org.hipparchus.distribution;

import org.hipparchus.exception.MathIllegalArgumentException;

/**
 * Base interface for multivariate continuous distributions.
 * 

* This is based largely on the RealDistribution interface, but cumulative * distribution functions are not required because they are often quite * difficult to compute for multivariate distributions. */ public interface MultivariateRealDistribution { /** * Returns the probability density function (PDF) of this distribution * evaluated at the specified point {@code x}. In general, the PDF is the * derivative of the cumulative distribution function. If the derivative * does not exist at {@code x}, then an appropriate replacement should be * returned, e.g. {@code Double.POSITIVE_INFINITY}, {@code Double.NaN}, or * the limit inferior or limit superior of the difference quotient. * * @param x Point at which the PDF is evaluated. * @return the value of the probability density function at point {@code x}. */ double density(double[] x); /** * Reseeds the random generator used to generate samples. * * @param seed Seed with which to initialize the random number generator. */ void reseedRandomGenerator(long seed); /** * Gets the number of random variables of the distribution. * It is the size of the array returned by the {@link #sample() sample} * method. * * @return the number of variables. */ int getDimension(); /** * Generates a random value vector sampled from this distribution. * * @return a random value vector. */ double[] sample(); /** * Generates a list of a random value vectors from the distribution. * * @param sampleSize the number of random vectors to generate. * @return an array representing the random samples. * @throws org.hipparchus.exception.MathIllegalArgumentException * if {@code sampleSize} is not positive. * * @see #sample() */ double[][] sample(int sampleSize) throws MathIllegalArgumentException; }





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