blob: e540c806c00e59e52308eeb58b0e50efe3b8d093 [file] [log] [blame]
/*
* 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.statistics.distribution;
import org.apache.commons.rng.UniformRandomProvider;
/**
* Implementation of the <a href="http://en.wikipedia.org/wiki/Chi-squared_distribution">chi-squared distribution</a>.
*/
public class ChiSquaredDistribution extends AbstractContinuousDistribution {
/** Internal Gamma distribution. */
private final GammaDistribution gamma;
/**
* Creates a distribution.
*
* @param degreesOfFreedom Degrees of freedom.
* @throws IllegalArgumentException if {@code degreesOfFreedom <= 0}.
*/
public ChiSquaredDistribution(double degreesOfFreedom) {
gamma = new GammaDistribution(degreesOfFreedom / 2, 2);
}
/**
* Access the number of degrees of freedom.
*
* @return the degrees of freedom.
*/
public double getDegreesOfFreedom() {
return gamma.getShape() * 2;
}
/** {@inheritDoc} */
@Override
public double density(double x) {
return gamma.density(x);
}
/** {@inheritDoc} **/
@Override
public double logDensity(double x) {
return gamma.logDensity(x);
}
/** {@inheritDoc} */
@Override
public double cumulativeProbability(double x) {
return gamma.cumulativeProbability(x);
}
/** {@inheritDoc} */
@Override
public double survivalProbability(double x) {
return gamma.survivalProbability(x);
}
/**
* {@inheritDoc}
*
* <p>For {@code k} degrees of freedom, the mean is {@code k}.
*/
@Override
public double getMean() {
return getDegreesOfFreedom();
}
/**
* {@inheritDoc}
*
* @return {@code 2 * k}, where {@code k} is the number of degrees of freedom.
*/
@Override
public double getVariance() {
return 2 * getDegreesOfFreedom();
}
/**
* {@inheritDoc}
*
* <p>The lower bound of the support is always 0 no matter the
* degrees of freedom.
*
* @return zero.
*/
@Override
public double getSupportLowerBound() {
return 0;
}
/**
* {@inheritDoc}
*
* <p>The upper bound of the support is always positive infinity no matter the
* degrees of freedom.
*
* @return {@code Double.POSITIVE_INFINITY}.
*/
@Override
public double getSupportUpperBound() {
return Double.POSITIVE_INFINITY;
}
/**
* {@inheritDoc}
*
* <p>The support of this distribution is connected.
*
* @return {@code true}
*/
@Override
public boolean isSupportConnected() {
return true;
}
/**
* {@inheritDoc}
*
* <p>
* Sampling algorithms:
* <ul>
* <li>
* For {@code 0 < degreesOfFreedom < 2}:
* <blockquote>
* Ahrens, J. H. and Dieter, U.,
* <i>Computer methods for sampling from gamma, beta, Poisson and binomial distributions,</i>
* Computing, 12, 223-246, 1974.
* </blockquote>
* </li>
* <li>
* For {@code degreesOfFreedom >= 2}:
* <blockquote>
* Marsaglia and Tsang, <i>A Simple Method for Generating
* Gamma Variables.</i> ACM Transactions on Mathematical Software,
* Volume 26 Issue 3, September, 2000.
* </blockquote>
* </li>
* </ul>
*/
@Override
public ContinuousDistribution.Sampler createSampler(final UniformRandomProvider rng) {
return gamma.createSampler(rng);
}
}