From 93a6d754cc1ca0fc245e411d4b2d02058d3d4fc7 Mon Sep 17 00:00:00 2001 From: Brent Worden Date: Thu, 17 Mar 2005 03:20:12 +0000 Subject: [PATCH] added weibull distribution git-svn-id: https://svn.apache.org/repos/asf/jakarta/commons/proper/math/trunk@157874 13f79535-47bb-0310-9956-ffa450edef68 --- .../distribution/CauchyDistributionImpl.java | 6 +- .../distribution/DistributionFactory.java | 17 +- .../distribution/WeibullDistribution.java | 63 +++++++ .../distribution/WeibullDistributionImpl.java | 171 ++++++++++++++++++ .../DistributionFactoryImplTest.java | 48 +++++ .../distribution/WeibullDistributionTest.java | 113 ++++++++++++ xdocs/changes.xml | 3 + xdocs/userguide/distribution.xml | 1 + 8 files changed, 418 insertions(+), 4 deletions(-) create mode 100644 src/java/org/apache/commons/math/distribution/WeibullDistribution.java create mode 100644 src/java/org/apache/commons/math/distribution/WeibullDistributionImpl.java create mode 100644 src/test/org/apache/commons/math/distribution/WeibullDistributionTest.java diff --git a/src/java/org/apache/commons/math/distribution/CauchyDistributionImpl.java b/src/java/org/apache/commons/math/distribution/CauchyDistributionImpl.java index eea492e9b..cbcc22298 100644 --- a/src/java/org/apache/commons/math/distribution/CauchyDistributionImpl.java +++ b/src/java/org/apache/commons/math/distribution/CauchyDistributionImpl.java @@ -22,7 +22,7 @@ import java.io.Serializable; * Default implementation of * {@link org.apache.commons.math.distribution.CauchyDistribution}. * - * @version $Revision$ $Date$ + * @version $Revision: 1.13 $ $Date$ */ public class CauchyDistributionImpl extends AbstractContinuousDistribution implements CauchyDistribution, Serializable { @@ -37,8 +37,8 @@ public class CauchyDistributionImpl extends AbstractContinuousDistribution private double scale = 1; /** - * Creates normal distribution with the mean equal to zero and standard - * deviation equal to one. + * Creates cauchy distribution with the medain equal to zero and scale + * equal to one. */ public CauchyDistributionImpl(){ this(0.0, 1.0); diff --git a/src/java/org/apache/commons/math/distribution/DistributionFactory.java b/src/java/org/apache/commons/math/distribution/DistributionFactory.java index 0e60a613e..beb485276 100644 --- a/src/java/org/apache/commons/math/distribution/DistributionFactory.java +++ b/src/java/org/apache/commons/math/distribution/DistributionFactory.java @@ -32,6 +32,7 @@ import org.apache.commons.discovery.tools.DiscoverClass; *
  • Poisson
    • *
  • Normal
    • *
  • Student's t
    • + *
  • Weibull
    • * * * Common usage:
    @@ -175,8 +176,22 @@ public abstract class DistributionFactory {
      * Create a new Poisson distribution with poisson parameter lambda.
      * 
      * @param lambda poisson parameter
-     * @return a new normal distribution.  
+     * @return a new poisson distribution.  
      */               
     public abstract PoissonDistribution 
         createPoissonDistribution(double lambda);
+    
+    /**
+     * Create a new Weibull distribution with the given shape and scale
+     * parameters.
+     * 
+     * @param alpha the shape parameter.
+     * @param beta the scale parameter.
+     * @return a new Weibull distribution.  
+     */               
+    public WeibullDistribution createWeibullDistribution(
+        double alpha, double beta)
+    {
+        return new WeibullDistributionImpl(alpha, beta);
+    }
 }
diff --git a/src/java/org/apache/commons/math/distribution/WeibullDistribution.java b/src/java/org/apache/commons/math/distribution/WeibullDistribution.java
new file mode 100644
index 000000000..3333f051f
--- /dev/null
+++ b/src/java/org/apache/commons/math/distribution/WeibullDistribution.java
@@ -0,0 +1,63 @@
+/*
+ * Copyright 2005 The Apache Software Foundation.
+ *
+ * Licensed 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;
+
+/**
+ * Weibull Distribution.  This interface defines the two parameter form of the
+ * distribution as defined by
+ * 
+ * Weibull Distribution, equations (1) and (2).
+ *
+ * Instances of WeibullDistribution objects should be created using
+ * {@link DistributionFactory#createWeibullDistribution(double, double)}
+ *
+ * 
    
+ * References:
+ * 
    
+ * 
    
+ *
+ * @version $Revision: 1.12 $ $Date: 2004-06-23 11:26:18 -0500 (Wed, 23 Jun 2004) $
+ */
+public interface WeibullDistribution extends ContinuousDistribution {
+
+    /**
+     * Access the shape parameter.
+     * @return the shape parameter.
+     */
+    double getShape();
+    
+    /**
+     * Access the scale parameter.
+     * @return the scale parameter.
+     */
+    double getScale();
+    
+    /**
+     * Modify the shape parameter.
+     * @param alpha The new shape parameter value.
+     */
+    void setShape(double alpha);
+    
+    /**
+     * Modify the scale parameter.
+     * @param beta The new scale parameter value.
+     */
+    void setScale(double beta);
+}
diff --git a/src/java/org/apache/commons/math/distribution/WeibullDistributionImpl.java b/src/java/org/apache/commons/math/distribution/WeibullDistributionImpl.java
new file mode 100644
index 000000000..3d1dfef8b
--- /dev/null
+++ b/src/java/org/apache/commons/math/distribution/WeibullDistributionImpl.java
@@ -0,0 +1,171 @@
+/*
+ * Copyright 2005 The Apache Software Foundation.
+ *
+ * Licensed 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.WeibullDistribution}.
+ *
+ * @version $Revision: 1.13 $ $Date: 2004-07-24 16:41:37 -0500 (Sat, 24 Jul 2004) $
+ */
+public class WeibullDistributionImpl extends AbstractContinuousDistribution
+        implements WeibullDistribution, Serializable {
+    
+    /** Serializable version identifier */
+    static final long serialVersionUID = 8589540077390120676L;
+    
+    /** The shape parameter. */
+    private double alpha;
+    
+    /** The scale parameter. */
+    private double beta;
+    
+    /**
+     * Creates weibull distribution with the given shape and scale and a
+     * location equal to zero.
+     * @param alpha the shape parameter.
+     * @param beta the scale parameter.
+     */
+    public WeibullDistributionImpl(double alpha, double beta){
+        super();
+        setShape(alpha);
+        setScale(beta);
+    }
+
+    /**
+     * For this disbution, X, this method returns P(X < x).
+     * @param x the value at which the CDF is evaluated.
+     * @return CDF evaluted at x. 
+     */
+    public double cumulativeProbability(double x) {
+        double ret;
+        if (x <= 0.0) {
+            ret = 0.0;
+        } else {
+            ret = 1.0 - Math.exp(-Math.pow(x / getScale(), getShape()));
+        }
+        return ret;
+    }
+
+    /**
+     * Access alpha.
+     * @return the alpha.
+     */
+    public double getShape() {
+        return alpha;
+    }
+    
+    /**
+     * Access beta.
+     * @return the beta.
+     */
+    public double getScale() {
+        return beta;
+    }
+    
+    /**
+     * For this distribution, X, this method returns the critical point x, such
+     * that P(X < x) = p.
+     * 
    
+     * Returns Double.NEGATIVE_INFINITY for p=0 and 
+     * Double.POSITIVE_INFINITY for p=1.
+     *
+     * @param p the desired probability
+     * @return x, such that P(X < x) = p
+     * @throws IllegalArgumentException if p 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 = 0.0;
+        } else  if (p == 1) {
+            ret = Double.POSITIVE_INFINITY;
+        } else {
+            ret = getScale() * Math.pow(-Math.log(1.0 - p), 1.0 / getShape());
+        }
+        return ret;
+    }
+    
+    /**
+     * Modify alpha.
+     * @param alpha The new alpha value.
+     */
+    public void setShape(double alpha) {
+        if (alpha <= 0.0) {
+            throw new IllegalArgumentException(
+                "Shape must be positive.");
+        }       
+        this.alpha = alpha;
+    }
+    
+    /**
+     * Modify beta.
+     * @param beta The new beta value.
+     */
+    public void setScale(double beta) {
+        if (beta <= 0.0) {
+            throw new IllegalArgumentException(
+                "Scale must be positive.");
+        }       
+        this.beta = beta;
+    }
+
+    /**
+     * 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) {
+        // use median
+        return Math.pow(getScale() * Math.log(2.0), 1.0 / getShape());
+    }
+}
diff --git a/src/test/org/apache/commons/math/distribution/DistributionFactoryImplTest.java b/src/test/org/apache/commons/math/distribution/DistributionFactoryImplTest.java
index 479a97193..255930934 100644
--- a/src/test/org/apache/commons/math/distribution/DistributionFactoryImplTest.java
+++ b/src/test/org/apache/commons/math/distribution/DistributionFactoryImplTest.java
@@ -325,4 +325,52 @@ public class DistributionFactoryImplTest extends TestCase {
         } catch(IllegalArgumentException ex) {
         }
     }
+    
+    public void testCauchyDistributionNegative() {
+        try {
+            factory.createCauchyDistribution(0.0, -1.0);
+            fail("invalid scale. IllegalArgumentException expected");
+        } catch(IllegalArgumentException ex) {
+        }
+    }
+    
+    public void testCauchyDistributionZero() {
+        try {
+            factory.createCauchyDistribution(0.0, 0.0);
+            fail("invalid scale. IllegalArgumentException expected");
+        } catch(IllegalArgumentException ex) {
+        }
+    }
+    
+    public void testWeibullDistributionNegativePositive() {
+        try {
+            factory.createWeibullDistribution(-1.0, 1.0);
+            fail("invalid shape. IllegalArgumentException expected");
+        } catch(IllegalArgumentException ex) {
+        }
+    }
+    
+    public void testWeibullDistributionZeroPositive() {
+        try {
+            factory.createWeibullDistribution(0.0, 1.0);
+            fail("invalid shape. IllegalArgumentException expected");
+        } catch(IllegalArgumentException ex) {
+        }
+    }
+    
+    public void testWeibullDistributionPositiveNegative() {
+        try {
+            factory.createWeibullDistribution(1.0, -1.0);
+            fail("invalid scale. IllegalArgumentException expected");
+        } catch(IllegalArgumentException ex) {
+        }
+    }
+    
+    public void testWeibullDistributionPositiveZero() {
+        try {
+            factory.createWeibullDistribution(1.0, 0.0);
+            fail("invalid scale. IllegalArgumentException expected");
+        } catch(IllegalArgumentException ex) {
+        }
+    }
 }
diff --git a/src/test/org/apache/commons/math/distribution/WeibullDistributionTest.java b/src/test/org/apache/commons/math/distribution/WeibullDistributionTest.java
new file mode 100644
index 000000000..5ba7249de
--- /dev/null
+++ b/src/test/org/apache/commons/math/distribution/WeibullDistributionTest.java
@@ -0,0 +1,113 @@
+/*
+ * Copyright 2005 The Apache Software Foundation.
+ * 
+ * Licensed 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;
+
+/**
+ * Test cases for WeibullDistribution.
+ * Extends ContinuousDistributionAbstractTest.  See class javadoc for
+ * ContinuousDistributionAbstractTest for details.
+ * 
+ * @version $Revision: 1.8 $ $Date: 2004-07-24 16:41:37 -0500 (Sat, 24 Jul 2004) $
+ */
+public class WeibullDistributionTest extends ContinuousDistributionAbstractTest  {
+    
+    /**
+     * Constructor for CauchyDistributionTest.
+     * @param arg0
+     */
+    public WeibullDistributionTest(String arg0) {
+        super(arg0);
+    }
+    
+    //-------------- Implementations for abstract methods -----------------------
+    
+    /** Creates the default continuous distribution instance to use in tests. */
+    public ContinuousDistribution makeDistribution() {
+        return DistributionFactory.newInstance().createWeibullDistribution(1.2, 2.1);
+    }   
+    
+    /** Creates the default cumulative probability distribution test input values */
+    public double[] makeCumulativeTestPoints() {
+        // quantiles computed using Mathematica 
+        return new double[] {0.00664355181d, 0.04543282833d, 0.09811627374d,
+                0.1767135246d, 0.3219468654d, 4.207902826d, 5.23968437d,
+                6.232056007d, 7.497630467d, 10.51154969d};
+    }
+    
+    /** Creates the default cumulative probability density test expected values */
+    public double[] makeCumulativeTestValues() {
+        return new double[] {0.001d, 0.01d, 0.025d, 0.05d, 0.1d, 0.900d, 0.950d,
+                0.975d, 0.990d, 0.999d};
+    }
+    
+    //---------------------------- Additional test cases -------------------------
+    
+    public void testInverseCumulativeProbabilityExtremes() throws Exception {
+        setInverseCumulativeTestPoints(new double[] {0.0, 1.0});
+        setInverseCumulativeTestValues(
+                new double[] {0.0, Double.POSITIVE_INFINITY});
+        verifyInverseCumulativeProbabilities();
+    }
+    
+    public void testAlpha() {
+        WeibullDistribution distribution = (WeibullDistribution) getDistribution();
+        double expected = Math.random();
+        distribution.setShape(expected);
+        assertEquals(expected, distribution.getShape(), 0.0);
+    }
+    
+    public void testBeta() {
+        WeibullDistribution distribution = (WeibullDistribution) getDistribution();
+        double expected = Math.random();
+        distribution.setScale(expected);
+        assertEquals(expected, distribution.getScale(), 0.0);
+    }
+    
+    public void testSetAlpha() {
+        WeibullDistribution distribution = (WeibullDistribution) getDistribution();
+        try {
+            distribution.setShape(0.0);
+            fail("Can not have 0.0 alpha.");
+        } catch (IllegalArgumentException ex) {
+            // success
+        }
+        
+        try {
+            distribution.setShape(-1.0);
+            fail("Can not have negative alpha.");
+        } catch (IllegalArgumentException ex) {
+            // success
+        }
+    }
+    
+    public void testSetBeta() {
+        WeibullDistribution distribution = (WeibullDistribution) getDistribution();
+        try {
+            distribution.setScale(0.0);
+            fail("Can not have 0.0 beta.");
+        } catch (IllegalArgumentException ex) {
+            // success
+        }
+        
+        try {
+            distribution.setScale(-1.0);
+            fail("Can not have negative beta.");
+        } catch (IllegalArgumentException ex) {
+            // success
+        }
+    }
+}
diff --git a/xdocs/changes.xml b/xdocs/changes.xml
index 8b11e7776..b3294c3f2 100644
--- a/xdocs/changes.xml
+++ b/xdocs/changes.xml
@@ -39,6 +39,9 @@ The  type attribute can be add,update,fix,remove.
   
     
+      
+        Added Weibull distribution implementation.
+      
       
         Added Cauchy distribution implementation.
       
diff --git a/xdocs/userguide/distribution.xml b/xdocs/userguide/distribution.xml
index 0fd10ffbc..a953cb42a 100644
--- a/xdocs/userguide/distribution.xml
+++ b/xdocs/userguide/distribution.xml
@@ -63,6 +63,7 @@ BinomialDistribution binomial = factory.createBinomialDistribution(10, .75);Normal (Gaussian)createNormalDistribution
    Mean
    Standard Deviation
    
             PoissoncreatePoissonDistribution
    Mean
    
             tcreateTDistribution
    Degrees of freedom
    
+            WeibullcreateWeibullDistribution
    Shape
    Scale
    Location