001    /*
002     * Licensed to the Apache Software Foundation (ASF) under one or more
003     * contributor license agreements.  See the NOTICE file distributed with
004     * this work for additional information regarding copyright ownership.
005     * The ASF licenses this file to You under the Apache License, Version 2.0
006     * (the "License"); you may not use this file except in compliance with
007     * the License.  You may obtain a copy of the License at
008     *
009     *      http://www.apache.org/licenses/LICENSE-2.0
010     *
011     * Unless required by applicable law or agreed to in writing, software
012     * distributed under the License is distributed on an "AS IS" BASIS,
013     * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
014     * See the License for the specific language governing permissions and
015     * limitations under the License.
016     */
017    
018    package org.apache.commons.math.distribution;
019    
020    import java.io.Serializable;
021    
022    import org.apache.commons.math.MathRuntimeException;
023    
024    /**
025     * Default implementation of
026     * {@link org.apache.commons.math.distribution.WeibullDistribution}.
027     *
028     * @since 1.1
029     * @version $Revision: 772119 $ $Date: 2009-05-06 05:43:28 -0400 (Wed, 06 May 2009) $
030     */
031    public class WeibullDistributionImpl extends AbstractContinuousDistribution
032            implements WeibullDistribution, Serializable {
033        
034        /** Serializable version identifier */
035        private static final long serialVersionUID = 8589540077390120676L;
036        
037        /** The shape parameter. */
038        private double alpha;
039        
040        /** The scale parameter. */
041        private double beta;
042        
043        /**
044         * Creates weibull distribution with the given shape and scale and a
045         * location equal to zero.
046         * @param alpha the shape parameter.
047         * @param beta the scale parameter.
048         */
049        public WeibullDistributionImpl(double alpha, double beta){
050            super();
051            setShape(alpha);
052            setScale(beta);
053        }
054    
055        /**
056         * For this distribution, X, this method returns P(X &lt; <code>x</code>).
057         * @param x the value at which the CDF is evaluated.
058         * @return CDF evaluted at <code>x</code>. 
059         */
060        public double cumulativeProbability(double x) {
061            double ret;
062            if (x <= 0.0) {
063                ret = 0.0;
064            } else {
065                ret = 1.0 - Math.exp(-Math.pow(x / getScale(), getShape()));
066            }
067            return ret;
068        }
069    
070        /**
071         * Access the shape parameter.
072         * @return the shape parameter.
073         */
074        public double getShape() {
075            return alpha;
076        }
077        
078        /**
079         * Access the scale parameter.
080         * @return the scale parameter.
081         */
082        public double getScale() {
083            return beta;
084        }
085        
086        /**
087         * For this distribution, X, this method returns the critical point x, such
088         * that P(X &lt; x) = <code>p</code>.
089         * <p>
090         * Returns <code>Double.NEGATIVE_INFINITY</code> for p=0 and 
091         * <code>Double.POSITIVE_INFINITY</code> for p=1.</p>
092         *
093         * @param p the desired probability
094         * @return x, such that P(X &lt; x) = <code>p</code>
095         * @throws IllegalArgumentException if <code>p</code> is not a valid
096         *         probability.
097         */
098        @Override
099        public double inverseCumulativeProbability(double p) {
100            double ret;
101            if (p < 0.0 || p > 1.0) {
102                throw MathRuntimeException.createIllegalArgumentException(
103                      "{0} out of [{1}, {2}] range", p, 0.0, 1.0);
104            } else if (p == 0) {
105                ret = 0.0;
106            } else  if (p == 1) {
107                ret = Double.POSITIVE_INFINITY;
108            } else {
109                ret = getScale() * Math.pow(-Math.log(1.0 - p), 1.0 / getShape());
110            }
111            return ret;
112        }
113        
114        /**
115         * Modify the shape parameter.
116         * @param alpha the new shape parameter value.
117         */
118        public void setShape(double alpha) {
119            if (alpha <= 0.0) {
120                throw MathRuntimeException.createIllegalArgumentException(
121                      "shape must be positive ({0})",
122                      alpha);
123            }       
124            this.alpha = alpha;
125        }
126        
127        /**
128         * Modify the scale parameter.
129         * @param beta the new scale parameter value.
130         */
131        public void setScale(double beta) {
132            if (beta <= 0.0) {
133                throw MathRuntimeException.createIllegalArgumentException(
134                      "scale must be positive ({0})",
135                      beta);
136            }       
137            this.beta = beta;
138        }
139    
140        /**
141         * Access the domain value lower bound, based on <code>p</code>, used to
142         * bracket a CDF root.  This method is used by
143         * {@link #inverseCumulativeProbability(double)} to find critical values.
144         * 
145         * @param p the desired probability for the critical value
146         * @return domain value lower bound, i.e.
147         *         P(X &lt; <i>lower bound</i>) &lt; <code>p</code> 
148         */
149        @Override
150        protected double getDomainLowerBound(double p) {
151            return 0.0;
152        }
153    
154        /**
155         * Access the domain value upper bound, based on <code>p</code>, used to
156         * bracket a CDF root.  This method is used by
157         * {@link #inverseCumulativeProbability(double)} to find critical values.
158         * 
159         * @param p the desired probability for the critical value
160         * @return domain value upper bound, i.e.
161         *         P(X &lt; <i>upper bound</i>) &gt; <code>p</code> 
162         */
163        @Override
164        protected double getDomainUpperBound(double p) {
165            return Double.MAX_VALUE;
166        }
167    
168        /**
169         * Access the initial domain value, based on <code>p</code>, used to
170         * bracket a CDF root.  This method is used by
171         * {@link #inverseCumulativeProbability(double)} to find critical values.
172         * 
173         * @param p the desired probability for the critical value
174         * @return initial domain value
175         */
176        @Override
177        protected double getInitialDomain(double p) {
178            // use median
179            return Math.pow(getScale() * Math.log(2.0), 1.0 / getShape());
180        }
181    }