Commons Math example source code file (ChiSquaredDistributionImpl.java)

This example Commons Math source code file (ChiSquaredDistributionImpl.java) is included in the DevDaily.com "Java Source Code Warehouse" project. The intent of this project is to help you "Learn Java by Example" ^TM.

Java - Commons Math tags/keywords

abstractcontinuousdistribution, chisquareddistribution, chisquareddistributionimpl, chisquareddistributionimpl, default_inverse_absolute_accuracy, default_inverse_absolute_accuracy, deprecated, deprecated, gammadistribution, gammadistributionimpl, io, mathexception, override, override, serializable

The Commons Math ChiSquaredDistributionImpl.java source code

/*
 * 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;

/**
 * The default implementation of {@link ChiSquaredDistribution}
 *
 * @version $Revision: 925812 $ $Date: 2010-03-21 11:49:31 -0400 (Sun, 21 Mar 2010) $
 */
public class ChiSquaredDistributionImpl
    extends AbstractContinuousDistribution
    implements ChiSquaredDistribution, 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 = -8352658048349159782L;

    /** Internal Gamma distribution. */
    private GammaDistribution gamma;

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

    /**
     * Create a Chi-Squared distribution with the given degrees of freedom.
     * @param df degrees of freedom.
     */
    public ChiSquaredDistributionImpl(double df) {
        this(df, new GammaDistributionImpl(df / 2.0, 2.0));
    }

    /**
     * Create a Chi-Squared distribution with the given degrees of freedom.
     * @param df degrees of freedom.
     * @param g the underlying gamma distribution used to compute probabilities.
     * @since 1.2
     * @deprecated as of 2.1 (to avoid possibly inconsistent state, the
     * "GammaDistribution" will be instantiated internally)
     */
    @Deprecated
    public ChiSquaredDistributionImpl(double df, GammaDistribution g) {
        super();
        setGammaInternal(g);
        setDegreesOfFreedomInternal(df);
        solverAbsoluteAccuracy = DEFAULT_INVERSE_ABSOLUTE_ACCURACY;
    }

    /**
     * Create a Chi-Squared distribution with the given degrees of freedom and
     * inverse cumulative probability accuracy.
     * @param df 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 ChiSquaredDistributionImpl(double df, double inverseCumAccuracy) {
        super();
        gamma = new GammaDistributionImpl(df / 2.0, 2.0);
        setDegreesOfFreedomInternal(df);
        solverAbsoluteAccuracy = inverseCumAccuracy;
    }

    /**
     * Modify the degrees of freedom.
     * @param degreesOfFreedom the new degrees of freedom.
     * @deprecated as of 2.1 (class will become immutable in 3.0)
     */
    @Deprecated
    public void setDegreesOfFreedom(double degreesOfFreedom) {
        setDegreesOfFreedomInternal(degreesOfFreedom);
    }
    /**
     * Modify the degrees of freedom.
     * @param degreesOfFreedom the new degrees of freedom.
     */
    private void setDegreesOfFreedomInternal(double degreesOfFreedom) {
        gamma.setAlpha(degreesOfFreedom / 2.0);
    }

    /**
     * Access the degrees of freedom.
     * @return the degrees of freedom.
     */
    public double getDegreesOfFreedom() {
        return gamma.getAlpha() * 2.0;
    }

    /**
     * Return the probability density for a particular point.
     *
     * @param x The point at which the density should be computed.
     * @return The pdf at point x.
     * @deprecated
     */
    public double density(Double x) {
        return density(x.doubleValue());
    }

    /**
     * Return 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) {
        return gamma.density(x);
    }

    /**
     * For this distribution, X, this method returns P(X < x).
     * @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 {
        return gamma.cumulativeProbability(x);
    }

    /**
     * For this distribution, X, this method returns the critical point x, such
     * that P(X < x) = <code>p.
     * <p>
     * Returns 0 for p=0 and <code>Double.POSITIVE_INFINITY for p=1.

     *
     * @param p the desired probability
     * @return x, such that P(X < x) = <code>p
     * @throws MathException if the inverse cumulative probability can not be
     *         computed due to convergence or other numerical errors.
     * @throws IllegalArgumentException if <code>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 <code>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 < <i>lower bound) < p
     */
    @Override
    protected double getDomainLowerBound(double p) {
        return Double.MIN_VALUE * gamma.getBeta();
    }

    /**
     * Access the domain value upper bound, based on <code>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 < <i>upper bound) > p
     */
    @Override
    protected double getDomainUpperBound(double p) {
        // NOTE: chi squared is skewed to the left
        // NOTE: therefore, P(X < μ) > .5

        double ret;

        if (p < .5) {
            // use mean
            ret = getDegreesOfFreedom();
        } else {
            // use max
            ret = Double.MAX_VALUE;
        }

        return ret;
    }

    /**
     * Access the initial domain value, based on <code>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) {
        // NOTE: chi squared is skewed to the left
        // NOTE: therefore, P(X < μ) > .5

        double ret;

        if (p < .5) {
            // use 1/2 mean
            ret = getDegreesOfFreedom() * .5;
        } else {
            // use mean
            ret = getDegreesOfFreedom();
        }

        return ret;
    }

    /**
     * Modify the underlying gamma distribution.  The caller is responsible for
     * insuring the gamma distribution has the proper parameter settings.
     * @param g the new distribution.
     * @since 1.2 made public
     * @deprecated as of 2.1 (class will become immutable in 3.0)
     */
    @Deprecated
    public void setGamma(GammaDistribution g) {
        setGammaInternal(g);
    }
    /**
     * Modify the underlying gamma distribution.  The caller is responsible for
     * insuring the gamma distribution has the proper parameter settings.
     * @param g the new distribution.
     * @since 1.2 made public
     */
    private void setGammaInternal(GammaDistribution g) {
        this.gamma = g;

    }


    /**
     * 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;
    }
}