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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.math.distribution;

import java.io.Serializable;

import org.apache.commons.math.MathException;
import org.apache.commons.math.MathRuntimeException;
import org.apache.commons.math.exception.util.LocalizedFormats;
import org.apache.commons.math.special.Beta;
import org.apache.commons.math.util.FastMath;

/**
 * Default implementation of
 * {@link org.apache.commons.math.distribution.FDistribution}.
 *
 * @version $Revision: 1054524 $ $Date: 2011-01-03 05:59:18 +0100 (lun. 03 janv. 2011) $
 */
public class FDistributionImpl
    extends AbstractContinuousDistribution
    implements FDistribution, Serializable  {

    /**
     * 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 double numeratorDegreesOfFreedom;

    /** The numerator degrees of freedom*/
    private double denominatorDegreesOfFreedom;

    /** Inverse cumulative probability accuracy */
    private final double solverAbsoluteAccuracy;

    /**
     * Create a F distribution using the given degrees of freedom.
     * @param numeratorDegreesOfFreedom the numerator degrees of freedom.
     * @param denominatorDegreesOfFreedom the denominator degrees of freedom.
     */
    public FDistributionImpl(double numeratorDegreesOfFreedom,
                             double denominatorDegreesOfFreedom) {
        this(numeratorDegreesOfFreedom, denominatorDegreesOfFreedom, DEFAULT_INVERSE_ABSOLUTE_ACCURACY);
    }

    /**
     * Create a F distribution using the given degrees of freedom and inverse cumulative probability accuracy.
     * @param numeratorDegreesOfFreedom the numerator degrees of freedom.
     * @param denominatorDegreesOfFreedom the denominator degrees of freedom.
     * @param inverseCumAccuracy the maximum absolute error in inverse cumulative probability estimates
     * (defaults to {@link #DEFAULT_INVERSE_ABSOLUTE_ACCURACY})
     * @since 2.1
     */
    public FDistributionImpl(double numeratorDegreesOfFreedom, double denominatorDegreesOfFreedom,
            double inverseCumAccuracy) {
        super();
        setNumeratorDegreesOfFreedomInternal(numeratorDegreesOfFreedom);
        setDenominatorDegreesOfFreedomInternal(denominatorDegreesOfFreedom);
        solverAbsoluteAccuracy = inverseCumAccuracy;
    }

    /**
     * Returns the probability density for a particular point.
     *
     * @param x The point at which the density should be computed.
     * @return The pdf at point x.
     * @since 2.1
     */
    @Override
    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));
    }

    /**
     * For this distribution, X, this method returns P(X < x).
     *
     * The implementation of this method is based on:
     * 
     *
     * @param x the value at which the CDF is evaluated.
     * @return CDF for this distribution.
     * @throws MathException if the cumulative probability can not be
     *            computed due to convergence or other numerical errors.
     */
    public double cumulativeProbability(double x) throws MathException {
        double ret;
        if (x <= 0.0) {
            ret = 0.0;
        } else {
            double n = numeratorDegreesOfFreedom;
            double m = denominatorDegreesOfFreedom;

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

    /**
     * For this distribution, X, this method returns the critical point x, such
     * that P(X < x) = p.
     * 

* Returns 0 for p=0 and Double.POSITIVE_INFINITY for p=1.

* * @param p the desired probability * @return x, such that P(X < x) = p * @throws MathException if the inverse cumulative probability can not be * computed due to convergence or other numerical errors. * @throws IllegalArgumentException if p is not a valid * probability. */ @Override public double inverseCumulativeProbability(final double p) throws MathException { if (p == 0) { return 0d; } if (p == 1) { return Double.POSITIVE_INFINITY; } return super.inverseCumulativeProbability(p); } /** * Access the domain value lower bound, based on p, used to * bracket a CDF root. This method is used by * {@link #inverseCumulativeProbability(double)} to find critical values. * * @param p the desired probability for the critical value * @return domain value lower bound, i.e. * P(X < lower bound) < p */ @Override protected double getDomainLowerBound(double p) { return 0.0; } /** * Access the domain value upper bound, based on p, used to * bracket a CDF root. This method is used by * {@link #inverseCumulativeProbability(double)} to find critical values. * * @param p the desired probability for the critical value * @return domain value upper bound, i.e. * P(X < upper bound) > p */ @Override protected double getDomainUpperBound(double p) { return Double.MAX_VALUE; } /** * Access the initial domain value, based on p, used to * bracket a CDF root. This method is used by * {@link #inverseCumulativeProbability(double)} to find critical values. * * @param p the desired probability for the critical value * @return initial domain value */ @Override protected double getInitialDomain(double p) { double ret = 1.0; double d = denominatorDegreesOfFreedom; if (d > 2.0) { // use mean ret = d / (d - 2.0); } return ret; } /** * Modify the numerator degrees of freedom. * @param degreesOfFreedom the new numerator degrees of freedom. * @throws IllegalArgumentException if degreesOfFreedom is not * positive. * @deprecated as of 2.1 (class will become immutable in 3.0) */ @Deprecated public void setNumeratorDegreesOfFreedom(double degreesOfFreedom) { setNumeratorDegreesOfFreedomInternal(degreesOfFreedom); } /** * Modify the numerator degrees of freedom. * @param degreesOfFreedom the new numerator degrees of freedom. * @throws IllegalArgumentException if degreesOfFreedom is not * positive. */ private void setNumeratorDegreesOfFreedomInternal(double degreesOfFreedom) { if (degreesOfFreedom <= 0.0) { throw MathRuntimeException.createIllegalArgumentException( LocalizedFormats.NOT_POSITIVE_DEGREES_OF_FREEDOM, degreesOfFreedom); } this.numeratorDegreesOfFreedom = degreesOfFreedom; } /** * Access the numerator degrees of freedom. * @return the numerator degrees of freedom. */ public double getNumeratorDegreesOfFreedom() { return numeratorDegreesOfFreedom; } /** * Modify the denominator degrees of freedom. * @param degreesOfFreedom the new denominator degrees of freedom. * @throws IllegalArgumentException if degreesOfFreedom is not * positive. * @deprecated as of 2.1 (class will become immutable in 3.0) */ @Deprecated public void setDenominatorDegreesOfFreedom(double degreesOfFreedom) { setDenominatorDegreesOfFreedomInternal(degreesOfFreedom); } /** * Modify the denominator degrees of freedom. * @param degreesOfFreedom the new denominator degrees of freedom. * @throws IllegalArgumentException if degreesOfFreedom is not * positive. */ private void setDenominatorDegreesOfFreedomInternal(double degreesOfFreedom) { if (degreesOfFreedom <= 0.0) { throw MathRuntimeException.createIllegalArgumentException( LocalizedFormats.NOT_POSITIVE_DEGREES_OF_FREEDOM, degreesOfFreedom); } this.denominatorDegreesOfFreedom = degreesOfFreedom; } /** * Access the denominator degrees of freedom. * @return the denominator degrees of freedom. */ public double getDenominatorDegreesOfFreedom() { return denominatorDegreesOfFreedom; } /** * Return the absolute accuracy setting of the solver used to estimate * inverse cumulative probabilities. * * @return the solver absolute accuracy * @since 2.1 */ @Override protected double getSolverAbsoluteAccuracy() { return solverAbsoluteAccuracy; } /** * Returns the lower bound of the support for the distribution. * * The lower bound of the support is always 0, regardless of the parameters. * * @return lower bound of the support (always 0) * @since 2.2 */ public double getSupportLowerBound() { return 0; } /** * Returns the upper bound of the support for the distribution. * * The upper bound of the support is always positive infinity, * regardless of the parameters. * * @return upper bound of the support (always Double.POSITIVE_INFINITY) * @since 2.2 */ public double getSupportUpperBound() { return Double.POSITIVE_INFINITY; } /** * Returns the mean of the distribution. * * For denominator degrees of freedom parameter b, * the mean is *
    *
  • if b > 2 then b / (b - 2)
  • *
  • else undefined *
* * @return the mean * @since 2.2 */ public double getNumericalMean() { final double denominatorDF = getDenominatorDegreesOfFreedom(); if (denominatorDF > 2) { return denominatorDF / (denominatorDF - 2); } return Double.NaN; } /** * Returns the variance of the distribution. * * For numerator degrees of freedom parameter a * and denominator degrees of freedom parameter b, * the variance is *
    *
  • * if b > 4 then * [ 2 * b^2 * (a + b - 2) ] / [ a * (b - 2)^2 * (b - 4) ] *
  • *
  • else undefined *
* * @return the variance * @since 2.2 */ public double getNumericalVariance() { 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; } }




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