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Statistical sampling library for use in virtdata libraries, based on apache commons math 4

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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.
 */

package org.apache.commons.statistics.distribution;

import org.apache.commons.numbers.gamma.LogBeta;
import org.apache.commons.numbers.gamma.RegularizedBeta;

/**
 * Implementation of the F-distribution.
 *
 * @see F-distribution (Wikipedia)
 * @see F-distribution (MathWorld)
 */
public class FDistribution extends AbstractContinuousDistribution {
    /** The numerator degrees of freedom. */
    private final double numeratorDegreesOfFreedom;
    /** The numerator degrees of freedom. */
    private final double denominatorDegreesOfFreedom;

    /**
     * Creates a distribution.
     *
     * @param numeratorDegreesOfFreedom Numerator degrees of freedom.
     * @param denominatorDegreesOfFreedom Denominator degrees of freedom.
     * @throws IllegalArgumentException if {@code numeratorDegreesOfFreedom <= 0} or
     * {@code denominatorDegreesOfFreedom <= 0}.
     */
    public FDistribution(double numeratorDegreesOfFreedom,
                         double denominatorDegreesOfFreedom) {
        if (numeratorDegreesOfFreedom <= 0) {
            throw new DistributionException(DistributionException.NEGATIVE,
                                            numeratorDegreesOfFreedom);
        }
        if (denominatorDegreesOfFreedom <= 0) {
            throw new DistributionException(DistributionException.NEGATIVE,
                                            denominatorDegreesOfFreedom);
        }
        this.numeratorDegreesOfFreedom = numeratorDegreesOfFreedom;
        this.denominatorDegreesOfFreedom = denominatorDegreesOfFreedom;
    }

    /**
     * {@inheritDoc}
     */
    @Override
    public double density(double x) {
        return Math.exp(logDensity(x));
    }

    /** {@inheritDoc} **/
    @Override
    public double logDensity(double x) {
        final double nhalf = numeratorDegreesOfFreedom / 2;
        final double mhalf = denominatorDegreesOfFreedom / 2;
        final double logx = Math.log(x);
        final double logn = Math.log(numeratorDegreesOfFreedom);
        final double logm = Math.log(denominatorDegreesOfFreedom);
        final double lognxm = Math.log(numeratorDegreesOfFreedom * x +
                denominatorDegreesOfFreedom);
        return nhalf * logn + nhalf * logx - logx +
               mhalf * logm - nhalf * lognxm - mhalf * lognxm -
               LogBeta.value(nhalf, mhalf);
    }

    /**
     * {@inheritDoc}
     *
     * The implementation of this method is based on
     * 
     */
    @Override
    public double cumulativeProbability(double x)  {
        double ret;
        if (x <= 0) {
            ret = 0;
        } else {
            double n = numeratorDegreesOfFreedom;
            double m = denominatorDegreesOfFreedom;

            ret = RegularizedBeta.value((n * x) / (m + n * x),
                0.5 * n,
                0.5 * m);
        }
        return ret;
    }

    /**
     * Access the numerator degrees of freedom.
     *
     * @return the numerator degrees of freedom.
     */
    public double getNumeratorDegreesOfFreedom() {
        return numeratorDegreesOfFreedom;
    }

    /**
     * Access the denominator degrees of freedom.
     *
     * @return the denominator degrees of freedom.
     */
    public double getDenominatorDegreesOfFreedom() {
        return denominatorDegreesOfFreedom;
    }

    /**
     * {@inheritDoc}
     *
     * For denominator degrees of freedom parameter {@code b}, the mean is
     * 
    *
  • if {@code b > 2} then {@code b / (b - 2)},
  • *
  • else undefined ({@code Double.NaN}). *
*/ @Override public double getMean() { final double denominatorDF = getDenominatorDegreesOfFreedom(); if (denominatorDF > 2) { return denominatorDF / (denominatorDF - 2); } return Double.NaN; } /** * {@inheritDoc} * * For numerator degrees of freedom parameter {@code a} and denominator * degrees of freedom parameter {@code b}, the variance is *
    *
  • * if {@code b > 4} then * {@code [2 * b^2 * (a + b - 2)] / [a * (b - 2)^2 * (b - 4)]}, *
  • *
  • else undefined ({@code Double.NaN}). *
*/ @Override public double getVariance() { final double denominatorDF = getDenominatorDegreesOfFreedom(); if (denominatorDF > 4) { final double numeratorDF = getNumeratorDegreesOfFreedom(); final double denomDFMinusTwo = denominatorDF - 2; return (2 * (denominatorDF * denominatorDF) * (numeratorDF + denominatorDF - 2)) / ((numeratorDF * (denomDFMinusTwo * denomDFMinusTwo) * (denominatorDF - 4))); } return Double.NaN; } /** * {@inheritDoc} * * The lower bound of the support is always 0 no matter the parameters. * * @return lower bound of the support (always 0) */ @Override public double getSupportLowerBound() { return 0; } /** * {@inheritDoc} * * The upper bound of the support is always positive infinity * no matter the parameters. * * @return upper bound of the support (always Double.POSITIVE_INFINITY) */ @Override public double getSupportUpperBound() { return Double.POSITIVE_INFINITY; } /** * {@inheritDoc} * * The support of this distribution is connected. * * @return {@code true} */ @Override public boolean isSupportConnected() { return true; } }




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