cauchydistributionimpl.java

Apache的common math数学软件包

/*
 * 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;

/**
 * Default implementation of
 * {@link org.apache.commons.math.distribution.CauchyDistribution}.
 *
 * @since 1.1
 * @version $Revision: 617953 $ $Date: 2008-02-02 22:54:00 -0700 (Sat, 02 Feb 2008) $
 */
public class CauchyDistributionImpl extends AbstractContinuousDistribution 
        implements CauchyDistribution, Serializable {
    
    /** Serializable version identifier */
    private static final long serialVersionUID = 8589540077390120676L;

    /** The median of this distribution. */
    private double median = 0;
    
    /** The scale of this distribution. */
    private double scale = 1;
    
    /**
     * Creates cauchy distribution with the medain equal to zero and scale
     * equal to one. 
     */
    public CauchyDistributionImpl(){
        this(0.0, 1.0);
    }
    
    /**
     * Create a cauchy distribution using the given median and scale.
     * @param median median for this distribution
     * @param s scale parameter for this distribution
     */
    public CauchyDistributionImpl(double median, double s){
        super();
        setMedian(median);
        setScale(s);
    }

    /**
     * For this disbution, X, this method returns P(X &lt; <code>x</code>).
     * @param x the value at which the CDF is evaluated.
     * @return CDF evaluted at <code>x</code>. 
     */
    public double cumulativeProbability(double x) {
        return 0.5 + (Math.atan((x - median) / scale) / Math.PI);
    }
    
    /**
     * Access the median.
     * @return median for this distribution
     */ 
    public double getMedian() {
        return median;
    }

    /**
     * Access the scale parameter.
     * @return scale parameter for this distribution
     */
    public double getScale() {
        return scale;
    }
    
    /**
     * For this distribution, X, this method returns the critical point x, such
     * that P(X &lt; x) = <code>p</code>.
     * <p>
     * Returns <code>Double.NEGATIVE_INFINITY</code> for p=0 and 
     * <code>Double.POSITIVE_INFINITY</code> for p=1.</p>
     *
     * @param p the desired probability
     * @return x, such that P(X &lt; x) = <code>p</code>
     * @throws IllegalArgumentException if <code>p</code> is not a valid
     *         probability.
     */
    public double inverseCumulativeProbability(double p) {
        double ret;
        if (p < 0.0 || p > 1.0) {
            throw new IllegalArgumentException
                ("probability argument must be between 0 and 1 (inclusive)");
        } else if (p == 0) {
            ret = Double.NEGATIVE_INFINITY;
        } else  if (p == 1) {
            ret = Double.POSITIVE_INFINITY;
        } else {
            ret = median + scale * Math.tan(Math.PI * (p - .5));
        }
        return ret;
    }
    
    /**
     * Modify the median.
     * @param median for this distribution
     */
    public void setMedian(double median) {
        this.median = median;
    }

    /**
     * Modify the scale parameter.
     * @param s scale parameter for this distribution
     * @throws IllegalArgumentException if <code>sd</code> is not positive.
     */
    public void setScale(double s) {
        if (s <= 0.0) {
            throw new IllegalArgumentException(
                "Scale must be positive.");
        }       
        scale = s;
    }
    
    /**
     * Access the domain value lower bound, based on <code>p</code>, 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 &lt; <i>lower bound</i>) &lt; <code>p</code> 
     */
    protected double getDomainLowerBound(double p) {
        double ret;

        if (p < .5) {
            ret = -Double.MAX_VALUE;
        } else {
            ret = getMedian();
        }
        
        return ret;
    }

    /**
     * Access the domain value upper bound, based on <code>p</code>, 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 &lt; <i>upper bound</i>) &gt; <code>p</code> 
     */
    protected double getDomainUpperBound(double p) {
        double ret;

        if (p < .5) {
            ret = getMedian();
        } else {
            ret = Double.MAX_VALUE;
        }
        
        return ret;
    }

    /**
     * Access the initial domain value, based on <code>p</code>, 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;

        if (p < .5) {
            ret = getMedian() - getScale();
        } else if (p > .5) {
            ret = getMedian() + getScale();
        } else {
            ret = getMedian();
        }
        
        return ret;
    }
}