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The Apache Commons Math project is a library of lightweight, self-contained mathematics and statistics components addressing the most common practical problems not immediately available in the Java programming language or commons-lang.

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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.math3.distribution;

import org.apache.commons.math3.exception.NotStrictlyPositiveException;
import org.apache.commons.math3.exception.util.LocalizedFormats;
import org.apache.commons.math3.special.Beta;
import org.apache.commons.math3.util.FastMath;
import org.apache.commons.math3.random.RandomGenerator;
import org.apache.commons.math3.random.Well19937c;

/**
 * Implementation of the F-distribution.
 *
 * @see F-distribution (Wikipedia)
 * @see F-distribution (MathWorld)
 * @version $Id: FDistribution.java 1416643 2012-12-03 19:37:14Z tn $
 */
public class FDistribution extends AbstractRealDistribution {
    /**
     * Default inverse cumulative probability accuracy.
     * @since 2.1
     */
    public static final double DEFAULT_INVERSE_ABSOLUTE_ACCURACY = 1e-9;
    /** Serializable version identifier. */
    private static final long serialVersionUID = -8516354193418641566L;
    /** The numerator degrees of freedom. */
    private final double numeratorDegreesOfFreedom;
    /** The numerator degrees of freedom. */
    private final double denominatorDegreesOfFreedom;
    /** Inverse cumulative probability accuracy. */
    private final double solverAbsoluteAccuracy;
    /** Cached numerical variance */
    private double numericalVariance = Double.NaN;
    /** Whether or not the numerical variance has been calculated */
    private boolean numericalVarianceIsCalculated = false;

    /**
     * Creates an F distribution using the given degrees of freedom.
     *
     * @param numeratorDegreesOfFreedom Numerator degrees of freedom.
     * @param denominatorDegreesOfFreedom Denominator degrees of freedom.
     * @throws NotStrictlyPositiveException if
     * {@code numeratorDegreesOfFreedom <= 0} or
     * {@code denominatorDegreesOfFreedom <= 0}.
     */
    public FDistribution(double numeratorDegreesOfFreedom,
                         double denominatorDegreesOfFreedom)
        throws NotStrictlyPositiveException {
        this(numeratorDegreesOfFreedom, denominatorDegreesOfFreedom,
             DEFAULT_INVERSE_ABSOLUTE_ACCURACY);
    }

    /**
     * Creates an F distribution using the given degrees of freedom
     * and inverse cumulative probability accuracy.
     *
     * @param numeratorDegreesOfFreedom Numerator degrees of freedom.
     * @param denominatorDegreesOfFreedom Denominator degrees of freedom.
     * @param inverseCumAccuracy the maximum absolute error in inverse
     * cumulative probability estimates.
     * @throws NotStrictlyPositiveException if
     * {@code numeratorDegreesOfFreedom <= 0} or
     * {@code denominatorDegreesOfFreedom <= 0}.
     * @since 2.1
     */
    public FDistribution(double numeratorDegreesOfFreedom,
                         double denominatorDegreesOfFreedom,
                         double inverseCumAccuracy)
        throws NotStrictlyPositiveException {
        this(new Well19937c(), numeratorDegreesOfFreedom,
             denominatorDegreesOfFreedom, inverseCumAccuracy);
    }

    /**
     * Creates an F distribution.
     *
     * @param rng Random number generator.
     * @param numeratorDegreesOfFreedom Numerator degrees of freedom.
     * @param denominatorDegreesOfFreedom Denominator degrees of freedom.
     * @param inverseCumAccuracy the maximum absolute error in inverse
     * cumulative probability estimates.
     * @throws NotStrictlyPositiveException if
     * {@code numeratorDegreesOfFreedom <= 0} or
     * {@code denominatorDegreesOfFreedom <= 0}.
     * @since 3.1
     */
    public FDistribution(RandomGenerator rng,
                         double numeratorDegreesOfFreedom,
                         double denominatorDegreesOfFreedom,
                         double inverseCumAccuracy)
        throws NotStrictlyPositiveException {
        super(rng);

        if (numeratorDegreesOfFreedom <= 0) {
            throw new NotStrictlyPositiveException(LocalizedFormats.DEGREES_OF_FREEDOM,
                                                   numeratorDegreesOfFreedom);
        }
        if (denominatorDegreesOfFreedom <= 0) {
            throw new NotStrictlyPositiveException(LocalizedFormats.DEGREES_OF_FREEDOM,
                                                   denominatorDegreesOfFreedom);
        }
        this.numeratorDegreesOfFreedom = numeratorDegreesOfFreedom;
        this.denominatorDegreesOfFreedom = denominatorDegreesOfFreedom;
        solverAbsoluteAccuracy = inverseCumAccuracy;
    }

    /**
     * {@inheritDoc}
     *
     * @since 2.1
     */
    public double density(double x) {
        final double nhalf = numeratorDegreesOfFreedom / 2;
        final double mhalf = denominatorDegreesOfFreedom / 2;
        final double logx = FastMath.log(x);
        final double logn = FastMath.log(numeratorDegreesOfFreedom);
        final double logm = FastMath.log(denominatorDegreesOfFreedom);
        final double lognxm = FastMath.log(numeratorDegreesOfFreedom * x +
                                           denominatorDegreesOfFreedom);
        return FastMath.exp(nhalf * logn + nhalf * logx - logx +
                            mhalf * logm - nhalf * lognxm - mhalf * lognxm -
                            Beta.logBeta(nhalf, mhalf));
    }

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

            ret = Beta.regularizedBeta((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} */
    @Override
    protected double getSolverAbsoluteAccuracy() {
        return solverAbsoluteAccuracy;
    }

    /**
     * {@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}). *
*/ public double getNumericalMean() { 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}). *
*/ public double getNumericalVariance() { if (!numericalVarianceIsCalculated) { numericalVariance = calculateNumericalVariance(); numericalVarianceIsCalculated = true; } return numericalVariance; } /** * used by {@link #getNumericalVariance()} * * @return the variance of this distribution */ protected double calculateNumericalVariance() { 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) */ 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) */ public double getSupportUpperBound() { return Double.POSITIVE_INFINITY; } /** {@inheritDoc} */ public boolean isSupportLowerBoundInclusive() { return false; } /** {@inheritDoc} */ public boolean isSupportUpperBoundInclusive() { return false; } /** * {@inheritDoc} * * The support of this distribution is connected. * * @return {@code true} */ public boolean isSupportConnected() { return true; } }




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