added weibull distribution
git-svn-id: https://svn.apache.org/repos/asf/jakarta/commons/proper/math/trunk@157874 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Brent Worden
parent
9b4fe9da0a
commit
93a6d754cc
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@ -22,7 +22,7 @@ import java.io.Serializable;
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* Default implementation of
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* {@link org.apache.commons.math.distribution.CauchyDistribution}.
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*
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* @version $Revision$ $Date$
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* @version $Revision: 1.13 $ $Date$
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*/
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public class CauchyDistributionImpl extends AbstractContinuousDistribution
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implements CauchyDistribution, Serializable {
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@ -37,8 +37,8 @@ public class CauchyDistributionImpl extends AbstractContinuousDistribution
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private double scale = 1;
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/**
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* Creates normal distribution with the mean equal to zero and standard
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* deviation equal to one.
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* Creates cauchy distribution with the medain equal to zero and scale
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* equal to one.
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*/
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public CauchyDistributionImpl(){
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this(0.0, 1.0);
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@ -32,6 +32,7 @@ import org.apache.commons.discovery.tools.DiscoverClass;
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* <li>Poisson</li>
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* <li>Normal</li>
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* <li>Student's t</li>
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* <li>Weibull</li>
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* </ul>
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*
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* Common usage:<pre>
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@ -175,8 +176,22 @@ public abstract class DistributionFactory {
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* Create a new Poisson distribution with poisson parameter lambda.
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*
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* @param lambda poisson parameter
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* @return a new normal distribution.
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* @return a new poisson distribution.
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*/
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public abstract PoissonDistribution
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createPoissonDistribution(double lambda);
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/**
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* Create a new Weibull distribution with the given shape and scale
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* parameters.
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*
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* @param alpha the shape parameter.
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* @param beta the scale parameter.
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* @return a new Weibull distribution.
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*/
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public WeibullDistribution createWeibullDistribution(
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double alpha, double beta)
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{
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return new WeibullDistributionImpl(alpha, beta);
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}
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}
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@ -0,0 +1,63 @@
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/*
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* Copyright 2005 The Apache Software Foundation.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package org.apache.commons.math.distribution;
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/**
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* Weibull Distribution. This interface defines the two parameter form of the
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* distribution as defined by
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* <a href="http://mathworld.wolfram.com/WeibullDistribution.html">
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* Weibull Distribution</a>, equations (1) and (2).
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*
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* Instances of WeibullDistribution objects should be created using
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* {@link DistributionFactory#createWeibullDistribution(double, double)}
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*
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* <p>
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* References:
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* <ul>
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* <li><a href="http://mathworld.wolfram.com/WeibullDistribution.html">
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* Weibull Distribution</a></li>
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* </ul>
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* </p>
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*
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* @version $Revision: 1.12 $ $Date: 2004-06-23 11:26:18 -0500 (Wed, 23 Jun 2004) $
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*/
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public interface WeibullDistribution extends ContinuousDistribution {
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/**
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* Access the shape parameter.
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* @return the shape parameter.
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*/
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double getShape();
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/**
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* Access the scale parameter.
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* @return the scale parameter.
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*/
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double getScale();
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/**
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* Modify the shape parameter.
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* @param alpha The new shape parameter value.
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*/
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void setShape(double alpha);
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/**
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* Modify the scale parameter.
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* @param beta The new scale parameter value.
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*/
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void setScale(double beta);
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}
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@ -0,0 +1,171 @@
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/*
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* Copyright 2005 The Apache Software Foundation.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package org.apache.commons.math.distribution;
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import java.io.Serializable;
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/**
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* Default implementation of
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* {@link org.apache.commons.math.distribution.WeibullDistribution}.
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*
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* @version $Revision: 1.13 $ $Date: 2004-07-24 16:41:37 -0500 (Sat, 24 Jul 2004) $
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*/
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public class WeibullDistributionImpl extends AbstractContinuousDistribution
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implements WeibullDistribution, Serializable {
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/** Serializable version identifier */
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static final long serialVersionUID = 8589540077390120676L;
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/** The shape parameter. */
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private double alpha;
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/** The scale parameter. */
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private double beta;
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/**
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* Creates weibull distribution with the given shape and scale and a
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* location equal to zero.
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* @param alpha the shape parameter.
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* @param beta the scale parameter.
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*/
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public WeibullDistributionImpl(double alpha, double beta){
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super();
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setShape(alpha);
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setScale(beta);
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}
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/**
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* For this disbution, X, this method returns P(X < <code>x</code>).
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* @param x the value at which the CDF is evaluated.
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* @return CDF evaluted at <code>x</code>.
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*/
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public double cumulativeProbability(double x) {
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double ret;
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if (x <= 0.0) {
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ret = 0.0;
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} else {
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ret = 1.0 - Math.exp(-Math.pow(x / getScale(), getShape()));
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}
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return ret;
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}
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/**
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* Access alpha.
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* @return the alpha.
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*/
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public double getShape() {
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return alpha;
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}
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/**
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* Access beta.
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* @return the beta.
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*/
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public double getScale() {
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return beta;
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}
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/**
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* For this distribution, X, this method returns the critical point x, such
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* that P(X < x) = <code>p</code>.
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* <p>
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* Returns <code>Double.NEGATIVE_INFINITY</code> for p=0 and
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* <code>Double.POSITIVE_INFINITY</code> for p=1.
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*
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* @param p the desired probability
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* @return x, such that P(X < x) = <code>p</code>
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* @throws IllegalArgumentException if <code>p</code> is not a valid
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* probability.
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*/
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public double inverseCumulativeProbability(double p) {
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double ret;
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if (p < 0.0 || p > 1.0) {
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throw new IllegalArgumentException
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("probability argument must be between 0 and 1 (inclusive)");
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} else if (p == 0) {
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ret = 0.0;
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} else if (p == 1) {
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ret = Double.POSITIVE_INFINITY;
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} else {
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ret = getScale() * Math.pow(-Math.log(1.0 - p), 1.0 / getShape());
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}
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return ret;
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}
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/**
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* Modify alpha.
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* @param alpha The new alpha value.
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*/
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public void setShape(double alpha) {
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if (alpha <= 0.0) {
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throw new IllegalArgumentException(
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"Shape must be positive.");
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}
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this.alpha = alpha;
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}
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/**
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* Modify beta.
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* @param beta The new beta value.
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*/
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public void setScale(double beta) {
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if (beta <= 0.0) {
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throw new IllegalArgumentException(
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"Scale must be positive.");
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}
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this.beta = beta;
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}
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/**
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* Access the domain value lower bound, based on <code>p</code>, used to
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* bracket a CDF root. This method is used by
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* {@link #inverseCumulativeProbability(double)} to find critical values.
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*
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* @param p the desired probability for the critical value
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* @return domain value lower bound, i.e.
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* P(X < <i>lower bound</i>) < <code>p</code>
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*/
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protected double getDomainLowerBound(double p) {
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return 0.0;
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}
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/**
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* Access the domain value upper bound, based on <code>p</code>, used to
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* bracket a CDF root. This method is used by
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* {@link #inverseCumulativeProbability(double)} to find critical values.
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*
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* @param p the desired probability for the critical value
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* @return domain value upper bound, i.e.
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* P(X < <i>upper bound</i>) > <code>p</code>
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*/
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protected double getDomainUpperBound(double p) {
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return Double.MAX_VALUE;
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}
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/**
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* Access the initial domain value, based on <code>p</code>, used to
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* bracket a CDF root. This method is used by
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* {@link #inverseCumulativeProbability(double)} to find critical values.
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*
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* @param p the desired probability for the critical value
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* @return initial domain value
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*/
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protected double getInitialDomain(double p) {
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// use median
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return Math.pow(getScale() * Math.log(2.0), 1.0 / getShape());
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}
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}
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@ -325,4 +325,52 @@ public class DistributionFactoryImplTest extends TestCase {
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} catch(IllegalArgumentException ex) {
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}
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}
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public void testCauchyDistributionNegative() {
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try {
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factory.createCauchyDistribution(0.0, -1.0);
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fail("invalid scale. IllegalArgumentException expected");
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} catch(IllegalArgumentException ex) {
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}
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}
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public void testCauchyDistributionZero() {
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try {
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factory.createCauchyDistribution(0.0, 0.0);
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fail("invalid scale. IllegalArgumentException expected");
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} catch(IllegalArgumentException ex) {
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}
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}
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public void testWeibullDistributionNegativePositive() {
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try {
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factory.createWeibullDistribution(-1.0, 1.0);
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fail("invalid shape. IllegalArgumentException expected");
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} catch(IllegalArgumentException ex) {
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}
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}
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public void testWeibullDistributionZeroPositive() {
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try {
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factory.createWeibullDistribution(0.0, 1.0);
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fail("invalid shape. IllegalArgumentException expected");
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} catch(IllegalArgumentException ex) {
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}
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}
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public void testWeibullDistributionPositiveNegative() {
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try {
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factory.createWeibullDistribution(1.0, -1.0);
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fail("invalid scale. IllegalArgumentException expected");
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} catch(IllegalArgumentException ex) {
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}
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}
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public void testWeibullDistributionPositiveZero() {
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try {
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factory.createWeibullDistribution(1.0, 0.0);
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fail("invalid scale. IllegalArgumentException expected");
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} catch(IllegalArgumentException ex) {
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}
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}
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}
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@ -0,0 +1,113 @@
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/*
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* Copyright 2005 The Apache Software Foundation.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package org.apache.commons.math.distribution;
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/**
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* Test cases for WeibullDistribution.
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* Extends ContinuousDistributionAbstractTest. See class javadoc for
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* ContinuousDistributionAbstractTest for details.
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*
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* @version $Revision: 1.8 $ $Date: 2004-07-24 16:41:37 -0500 (Sat, 24 Jul 2004) $
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*/
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public class WeibullDistributionTest extends ContinuousDistributionAbstractTest {
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/**
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* Constructor for CauchyDistributionTest.
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* @param arg0
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*/
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public WeibullDistributionTest(String arg0) {
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super(arg0);
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}
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//-------------- Implementations for abstract methods -----------------------
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/** Creates the default continuous distribution instance to use in tests. */
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public ContinuousDistribution makeDistribution() {
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return DistributionFactory.newInstance().createWeibullDistribution(1.2, 2.1);
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}
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/** Creates the default cumulative probability distribution test input values */
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public double[] makeCumulativeTestPoints() {
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// quantiles computed using Mathematica
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return new double[] {0.00664355181d, 0.04543282833d, 0.09811627374d,
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0.1767135246d, 0.3219468654d, 4.207902826d, 5.23968437d,
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6.232056007d, 7.497630467d, 10.51154969d};
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}
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/** Creates the default cumulative probability density test expected values */
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public double[] makeCumulativeTestValues() {
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return new double[] {0.001d, 0.01d, 0.025d, 0.05d, 0.1d, 0.900d, 0.950d,
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0.975d, 0.990d, 0.999d};
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}
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//---------------------------- Additional test cases -------------------------
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public void testInverseCumulativeProbabilityExtremes() throws Exception {
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setInverseCumulativeTestPoints(new double[] {0.0, 1.0});
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setInverseCumulativeTestValues(
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new double[] {0.0, Double.POSITIVE_INFINITY});
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verifyInverseCumulativeProbabilities();
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}
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public void testAlpha() {
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WeibullDistribution distribution = (WeibullDistribution) getDistribution();
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double expected = Math.random();
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distribution.setShape(expected);
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assertEquals(expected, distribution.getShape(), 0.0);
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}
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public void testBeta() {
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WeibullDistribution distribution = (WeibullDistribution) getDistribution();
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double expected = Math.random();
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distribution.setScale(expected);
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assertEquals(expected, distribution.getScale(), 0.0);
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}
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public void testSetAlpha() {
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WeibullDistribution distribution = (WeibullDistribution) getDistribution();
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try {
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distribution.setShape(0.0);
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fail("Can not have 0.0 alpha.");
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} catch (IllegalArgumentException ex) {
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// success
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}
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try {
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distribution.setShape(-1.0);
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fail("Can not have negative alpha.");
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} catch (IllegalArgumentException ex) {
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// success
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}
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}
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public void testSetBeta() {
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WeibullDistribution distribution = (WeibullDistribution) getDistribution();
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try {
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distribution.setScale(0.0);
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fail("Can not have 0.0 beta.");
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} catch (IllegalArgumentException ex) {
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// success
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}
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try {
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distribution.setScale(-1.0);
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fail("Can not have negative beta.");
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} catch (IllegalArgumentException ex) {
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// success
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}
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}
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}
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@ -39,6 +39,9 @@ The <action> type attribute can be add,update,fix,remove.
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<body>
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<release version="1.1" date="In Development"
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description="Jakarta Commons Math 1.1 - Development">
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<action dev="brentworden" type="add">
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Added Weibull distribution implementation.
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</action>
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<action dev="brentworden" type="add">
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Added Cauchy distribution implementation.
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</action>
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@ -63,6 +63,7 @@ BinomialDistribution binomial = factory.createBinomialDistribution(10, .75);</so
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<tr><td>Normal (Gaussian)</td><td>createNormalDistribution</td><td><div>Mean</div><div>Standard Deviation</div></td></tr>
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<tr><td>Poisson</td><td>createPoissonDistribution</td><td><div>Mean</div></td></tr>
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<tr><td>t</td><td>createTDistribution</td><td><div>Degrees of freedom</div></td></tr>
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<tr><td>Weibull</td><td>createWeibullDistribution</td><td><div>Shape</div><div>Scale</div><div>Location</div></td></tr>
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</table>
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</p>
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<p>
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