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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.special.Beta;

/**
 * Default implementation of
 * {@link org.apache.commons.math.distribution.FDistribution}.
 *
 * @version $Revision$ $Date$
 */
public class FDistributionImpl
    extends AbstractContinuousDistribution
    implements FDistribution, Serializable  {

    /** 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;
    
    /**
     * 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) {
        super();
        setNumeratorDegreesOfFreedom(numeratorDegreesOfFreedom);
        setDenominatorDegreesOfFreedom(denominatorDegreesOfFreedom);
    }
    
    /**
     * 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 = getNumeratorDegreesOfFreedom();
            double m = getDenominatorDegreesOfFreedom();
            
            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. */ 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 */ 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 */ 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 */ protected double getInitialDomain(double p) { double ret; double d = getDenominatorDegreesOfFreedom(); // 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. */ public void setNumeratorDegreesOfFreedom(double degreesOfFreedom) { if (degreesOfFreedom <= 0.0) { throw new IllegalArgumentException( "degrees of freedom must be positive."); } 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. */ public void setDenominatorDegreesOfFreedom(double degreesOfFreedom) { if (degreesOfFreedom <= 0.0) { throw new IllegalArgumentException( "degrees of freedom must be positive."); } this.denominatorDegreesOfFreedom = degreesOfFreedom; } /** * Access the denominator degrees of freedom. * @return the denominator degrees of freedom. */ public double getDenominatorDegreesOfFreedom() { return denominatorDegreesOfFreedom; } }




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