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From mdigg...@apache.org
Subject cvs commit: jakarta-commons-sandbox/math/src/test/org/apache/commons/math/special BetaTest.java
Date Sat, 14 Jun 2003 04:17:49 GMT
mdiggory    2003/06/13 21:17:49

  Modified:    math/src/java/org/apache/commons/math/special Beta.java
               math/src/java/org/apache/commons/math/stat
                        UnivariateImpl.java
               math/src/java/org/apache/commons/math/stat/distribution
                        TDistributionImpl.java
               math/src/test/org/apache/commons/math/stat/distribution
                        TDistributionTest.java
  Added:       math/src/test/org/apache/commons/math/special BetaTest.java
  Log:
  PR: http://nagoya.apache.org/bugzilla/show_bug.cgi?id=20766
  Submitted by:	brent@worden.org
  
  Revision  Changes    Path
  1.3       +5 -15     jakarta-commons-sandbox/math/src/java/org/apache/commons/math/special/Beta.java
  
  Index: Beta.java
  ===================================================================
  RCS file: /home/cvs/jakarta-commons-sandbox/math/src/java/org/apache/commons/math/special/Beta.java,v
  retrieving revision 1.2
  retrieving revision 1.3
  diff -u -r1.2 -r1.3
  --- Beta.java	11 Jun 2003 01:19:18 -0000	1.2
  +++ Beta.java	14 Jun 2003 04:17:48 -0000	1.3
  @@ -139,17 +139,9 @@
       public static double regularizedBeta(double x, final double a, final double b, double
epsilon, int maxIterations) {
           double ret;
   
  -        if (a <= 0.0) {
  -            throw new IllegalArgumentException("a must be positive");
  -        } else if (b <= 0.0) {
  -            throw new IllegalArgumentException("b must be positive");
  -        } else if (x < 0.0 || x > 1.0) {
  -            throw new IllegalArgumentException(
  -                "x must be between 0.0 and 1.0, inclusive");
  -        } else if(x == 0.0){
  -            ret = 0.0;
  -        } else if(x == 1.0){
  -            ret = 1.0;
  +        if (Double.isNaN(x) || Double.isNaN(a) || Double.isNaN(b) || (x < 0)
  +                || (x > 1) || (a <= 0.0) || (b <= 0.0)) {
  +            ret = Double.NaN;
           } else {
               ContinuedFraction fraction = new ContinuedFraction() {
                   protected double getB(int n, double x) {
  @@ -228,10 +220,8 @@
       public static double logBeta(double a, double b, double epsilon, int maxIterations)
{
           double ret;
   
  -        if (a <= 0.0) {
  -            throw new IllegalArgumentException("a must be positive");
  -        } else if (b <= 0.0) {
  -            throw new IllegalArgumentException("b must be positive");
  +        if (Double.isNaN(a) || Double.isNaN(b) || (a <= 0.0) || (b <= 0.0)) {
  +            ret = Double.NaN;
           } else {
               ret = Gamma.logGamma(a, epsilon, maxIterations) + Gamma.logGamma(b, epsilon,
maxIterations)
                   - Gamma.logGamma(a + b, epsilon, maxIterations);
  
  
  
  1.4       +125 -119  jakarta-commons-sandbox/math/src/java/org/apache/commons/math/stat/UnivariateImpl.java
  
  Index: UnivariateImpl.java
  ===================================================================
  RCS file: /home/cvs/jakarta-commons-sandbox/math/src/java/org/apache/commons/math/stat/UnivariateImpl.java,v
  retrieving revision 1.3
  retrieving revision 1.4
  diff -u -r1.3 -r1.4
  --- UnivariateImpl.java	4 Jun 2003 12:23:44 -0000	1.3
  +++ UnivariateImpl.java	14 Jun 2003 04:17:49 -0000	1.4
  @@ -89,12 +89,12 @@
       /** running sum of squares that have been added */
       private double sumsq = 0.0;
   
  -	/** running sum of 3rd powers that have been added */
  -	private double sumCube = 0.0;
  -	
  -	/** running sum of 4th powers that have been added */
  -	private double sumQuad = 0.0;
  -	
  +    /** running sum of 3rd powers that have been added */
  +    private double sumCube = 0.0;
  +    
  +    /** running sum of 4th powers that have been added */
  +    private double sumQuad = 0.0;
  +    
       /** count of values that have been added */
       private int n = 0;
   
  @@ -120,17 +120,17 @@
   
        
       /**
  -	 * @see org.apache.commons.math.stat.Univariate#addValue(double)
  -	 */
  -	public void addValue(double v) {
  +     * @see org.apache.commons.math.stat.Univariate#addValue(double)
  +     */
  +    public void addValue(double v) {
           insertValue(v);
       }
   
       
       /**
  -	 * @see org.apache.commons.math.stat.Univariate#getMean()
  -	 */
  -	public double getMean() {
  +     * @see org.apache.commons.math.stat.Univariate#getMean()
  +     */
  +    public double getMean() {
           if (n == 0) {
               return Double.NaN;
           } else {
  @@ -140,97 +140,97 @@
   
        
       /**
  -	 * @see org.apache.commons.math.stat.Univariate#getGeometricMean()
  -	 */
  -	public double getGeometricMean() {
  +     * @see org.apache.commons.math.stat.Univariate#getGeometricMean()
  +     */
  +    public double getGeometricMean() {
           if ((product <= 0.0) || (n == 0)) {
               return Double.NaN; 
           } else {
  -            return Math.pow(product,( 1.0/(double)n ) );
  +            return Math.pow(product,( 1.0 / (double) n ) );
           }
       }
   
       /**
  -	 * @see org.apache.commons.math.stat.Univariate#getProduct()
  -	 */
  -	public double getProduct() {
  +     * @see org.apache.commons.math.stat.Univariate#getProduct()
  +     */
  +    public double getProduct() {
           return product;
       }
   
  -	/**
  -	 * @see org.apache.commons.math.stat.Univariate#getStandardDeviation()
  -	 */
  -	public double getStandardDeviation() {
  -		double variance = getVariance();
  -		if ((variance == 0.0) || (variance == Double.NaN)) {
  -			return variance;
  -		} else {
  -			return Math.sqrt(variance);
  -		}
  -	}
  -	
  -	/**
  -	 * Returns the variance of the values that have been added as described by
  -	 * <a href="http://mathworld.wolfram.com/k-Statistic.html">Equation (5) for k-Statistics</a>.
  -	 * 
  -	 * @return The variance of a set of values.  Double.NaN is returned for
  -	 *         an empty set of values and 0.0 is returned for a &lt;= 1 value set.
  -	 */
  -	public double getVariance() {
  -		double variance = Double.NaN;
  -
  -		if( n == 1 ) {
  -			variance = 0.0;
  -		} else if( n > 1 ) {
  -			variance = (((double)n)*sumsq - (sum * sum)) / (double) (n * (n - 1));	
  -		}
  +    /**
  +     * @see org.apache.commons.math.stat.Univariate#getStandardDeviation()
  +     */
  +    public double getStandardDeviation() {
  +        double variance = getVariance();
  +        if ((variance == 0.0) || (variance == Double.NaN)) {
  +            return variance;
  +        } else {
  +            return Math.sqrt(variance);
  +        }
  +    }
  +    
  +    /**
  +     * Returns the variance of the values that have been added as described by
  +     * <a href="http://mathworld.wolfram.com/k-Statistic.html">Equation (5) for k-Statistics</a>.
  +     * 
  +     * @return The variance of a set of values.  Double.NaN is returned for
  +     *         an empty set of values and 0.0 is returned for a &lt;= 1 value set.
  +     */
  +    public double getVariance() {
  +        double variance = Double.NaN;
   
  -		return variance < 0 ? 0.0 : variance;
  -	}
  +        if( n == 1 ) {
  +            variance = 0.0;
  +        } else if( n > 1 ) {
  +            variance = (((double) n) * sumsq - (sum * sum)) / (double) (n * (n - 1)); 
  
  +        }
  +
  +        return variance < 0 ? 0.0 : variance;
  +    }
        
  -	/**
  -	 * Returns the skewness of the values that have been added as described by
  +    /**
  +     * Returns the skewness of the values that have been added as described by
        * <a href="http://mathworld.wolfram.com/k-Statistic.html">Equation (6) for k-Statistics</a>.
        * 
  -	 * @return The skew of a set of values.  Double.NaN is returned for
  -	 *         an empty set of values and 0.0 is returned for a &lt;= 2 value set.
  -	 */
  -	public double getSkewness() {
  -		
  -		if( n < 1) return Double.NaN;
  -		if( n <= 2 ) return 0.0;                  
  -			
  -		return ( 2*Math.pow(sum,3) - 3*sum*sumsq + ((double)(n*n))*sumCube ) / 
  -			   ( (double)(n*(n-1)*(n-2)) ) ;  
  -	}
  -	
  -	/**
  -	 * Returns the kurtosis of the values that have been added as described by
  +     * @return The skew of a set of values.  Double.NaN is returned for
  +     *         an empty set of values and 0.0 is returned for a &lt;= 2 value set.
  +     */
  +    public double getSkewness() {
  +        
  +        if( n < 1) return Double.NaN;
  +        if( n <= 2 ) return 0.0;                  
  +            
  +        return ( 2 * Math.pow(sum, 3) - 3 * sum * sumsq + ((double) (n * n)) * sumCube
) / 
  +               ( (double) (n * (n - 1) * (n - 2)) ) ;  
  +    }
  +    
  +    /**
  +     * Returns the kurtosis of the values that have been added as described by
        * <a href="http://mathworld.wolfram.com/k-Statistic.html">Equation (7) for k-Statistics</a>.
        * 
  -	 * @return The kurtosis of a set of values.  Double.NaN is returned for
  -	 *         an empty set of values and 0.0 is returned for a &lt;= 3 value set.
  -	 */
  -	public double getKurtosis() {
  -		
  -		if( n < 1) return Double.NaN;
  -		if( n <= 3 ) return 0.0;
  -		
  -		double x1 = -6*Math.pow(sum,4);
  -		double x2 = 12*((double)n)*Math.pow(sum,2)*sumsq;
  -		double x3 = -3*((double)(n*(n-1)))*Math.pow(sumsq,2);
  -		double x4 = -4*((double)(n*(n+1)))*sum*sumCube;
  -		double x5 = Math.pow(((double)n),2)*((double)(n+1))*sumQuad;
  -		
  -		return (x1 + x2 + x3 + x4 + x5) / 
  -			   ( (double)(n*(n-1)*(n-2)*(n-3)) );
  -	} 
  -	
  +     * @return The kurtosis of a set of values.  Double.NaN is returned for
  +     *         an empty set of values and 0.0 is returned for a &lt;= 3 value set.
  +     */
  +    public double getKurtosis() {
  +        
  +        if( n < 1) return Double.NaN;
  +        if( n <= 3 ) return 0.0;
  +        
  +        double x1 = -6 * Math.pow(sum, 4);
  +        double x2 = 12 * ((double) n) * Math.pow(sum, 2) * sumsq;
  +        double x3 = -3 * ((double) (n * (n - 1))) * Math.pow(sumsq,2);
  +        double x4 = -4 * ((double) (n * (n + 1))) * sum * sumCube;
  +        double x5 = Math.pow(((double) n),2) * ((double) (n+1)) * sumQuad;
  +        
  +        return (x1 + x2 + x3 + x4 + x5) / 
  +               ( (double) (n * (n - 1) * (n - 2) * (n - 3)) );
  +    } 
  +    
       /**
        * Called in "addValue" to insert a new value into the statistic.
  -	 * @param v The value to be added.
  -	 */
  -	private void insertValue(double v) {
  +     * @param v The value to be added.
  +     */
  +    private void insertValue(double v) {
   
           // The default value of product is NaN, if you
           // try to retrieve the product for a univariate with
  @@ -250,34 +250,36 @@
                   // Remove the influence of the discarded
                   sum -= discarded;
                   sumsq -= discarded * discarded;
  -				sumCube -= Math.pow(discarded,3);
  -				sumQuad -= Math.pow(discarded,4); 
  -				
  +                sumCube -= Math.pow(discarded, 3);
  +                sumQuad -= Math.pow(discarded, 4); 
  +                
                   if(discarded == min) {
                       min = doubleArray.getMin();
  -                } else {
  -                    if(discarded == max){
  +                } else if(discarded == max){
                       max = doubleArray.getMax();
  -                    }
                   } 
                   
                   if(product != 0.0){
                       // can safely remove discarded value
  -                    product *= v/discarded;
  +                    product *=  v / discarded;
                   } else if(discarded == 0.0){
                       // need to recompute product
                       product = 1.0;
                       double[] elements = doubleArray.getElements();
                       for( int i = 0; i < elements.length; i++ ) {
  -                    	product *= elements[i];
  +                        product *= elements[i];
                       }
                   } // else product = 0 and will still be 0 after discard
   
               } else {
  -                doubleArray.addElement( v );        	
  +                doubleArray.addElement( v );            
                   n += 1.0;
  -                if (v < min) min = v;
  -                if (v > max) max = v;
  +                if (v < min) {
  +                    min = v;
  +                }
  +                if (v > max) {
  +                    max = v;
  +                }
                   product *= v;
               }
           } else {
  @@ -285,15 +287,19 @@
               // worry about storing any values.  We don't need to discard the
               // influence of any single item.
               n += 1.0;
  -            if (v < min) min = v;
  -            if (v > max) max = v;
  +            if (v < min) {
  +                min = v;
  +            } 
  +            if (v > max) {
  +                max = v;
  +            } 
               product *= v;
           }
           
  -		sum += v;
  -		sumsq += v*v;
  -		sumCube += Math.pow(v,3);
  -		sumQuad += Math.pow(v,4);
  +        sum += v;
  +        sumsq += v * v;
  +        sumCube += Math.pow(v,3);
  +        sumQuad += Math.pow(v,4);
       }
   
       /** Getter for property max.
  @@ -339,20 +345,20 @@
           return sumsq;
       }
   
  -	/** Getter for property sumCube.
  -	 * @return Value of property sumCube.
  -	 */
  -	public double getSumCube() {
  -		return sumCube;
  -	}
  -	
  -	/** Getter for property sumQuad.
  -	 * @return Value of property sumQuad.
  -	 */
  -	public double getSumQuad() {
  -		return sumQuad;
  -	}
  -	
  +    /** Getter for property sumCube.
  +     * @return Value of property sumCube.
  +     */
  +    public double getSumCube() {
  +        return sumCube;
  +    }
  +    
  +    /** Getter for property sumQuad.
  +     * @return Value of property sumQuad.
  +     */
  +    public double getSumQuad() {
  +        return sumQuad;
  +    }
  +    
       /**
        * Generates a text report displaying 
        * univariate statistics from values that
  @@ -367,8 +373,8 @@
           outBuffer.append("max: " + max + "\n");
           outBuffer.append("mean: " + getMean() + "\n");
           outBuffer.append("std dev: " + getStandardDeviation() + "\n");
  -		outBuffer.append("skewness: " + getSkewness() + "\n");
  -		outBuffer.append("kurtosis: " + getKurtosis() + "\n");
  +        outBuffer.append("skewness: " + getSkewness() + "\n");
  +        outBuffer.append("kurtosis: " + getKurtosis() + "\n");
           return outBuffer.toString();
       }
       
  
  
  
  1.2       +12 -9     jakarta-commons-sandbox/math/src/java/org/apache/commons/math/stat/distribution/TDistributionImpl.java
  
  Index: TDistributionImpl.java
  ===================================================================
  RCS file: /home/cvs/jakarta-commons-sandbox/math/src/java/org/apache/commons/math/stat/distribution/TDistributionImpl.java,v
  retrieving revision 1.1
  retrieving revision 1.2
  diff -u -r1.1 -r1.2
  --- TDistributionImpl.java	7 Jun 2003 13:57:54 -0000	1.1
  +++ TDistributionImpl.java	14 Jun 2003 04:17:49 -0000	1.2
  @@ -103,18 +103,21 @@
        * @return CDF evaluted at <code>x</code>. 
        */
       public double cummulativeProbability(double x) {
  -        double t = Beta.regularizedBeta(
  -            getDegreesOfFreedom() / (getDegreesOfFreedom() + (x * x)),
  -            0.5 * getDegreesOfFreedom(), 0.5);
  -            
           double ret;
  -        if(x < 0.0){
  -            ret = 0.5 * t;
  -        } else if(x > 0.0){
  -            ret = 1.0 - 0.5 * t;
  -        } else {
  +        if(x == 0.0){
               ret = 0.5;
  +        } else {
  +            double t = Beta.regularizedBeta(
  +                getDegreesOfFreedom() / (getDegreesOfFreedom() + (x * x)),
  +                0.5 * getDegreesOfFreedom(), 0.5);
  +                
  +            if(x < 0.0){
  +                ret = 0.5 * t;
  +            } else {
  +                ret = 1.0 - 0.5 * t;
  +            }
           }
  +        
           return ret;
       }
           
  
  
  
  1.2       +67 -19    jakarta-commons-sandbox/math/src/test/org/apache/commons/math/stat/distribution/TDistributionTest.java
  
  Index: TDistributionTest.java
  ===================================================================
  RCS file: /home/cvs/jakarta-commons-sandbox/math/src/test/org/apache/commons/math/stat/distribution/TDistributionTest.java,v
  retrieving revision 1.1
  retrieving revision 1.2
  diff -u -r1.1 -r1.2
  --- TDistributionTest.java	7 Jun 2003 13:57:54 -0000	1.1
  +++ TDistributionTest.java	14 Jun 2003 04:17:49 -0000	1.2
  @@ -85,45 +85,93 @@
           super.tearDown();
       }
   
  -    public void testLowerTailProbability(){
  +    public void testInverseCummulativeProbability001() {
  +        testValue(-5.893, .001);
  +    }
  +    
  +    public void testInverseCumulativeProbability010() {
  +        testValue(-3.365, .010);
  +    }
  +    
  +    public void testInverseCumulativeProbability025() {
  +        testValue(-2.571, .025);
  +    }
  +
  +    public void testInverseCumulativeProbability050() {
  +        testValue(-2.015, .050);
  +    }
  +    
  +    public void testInverseCumulativeProbability100() {
  +        testValue(-1.476, .100);
  +    }
  +
  +    public void testInverseCummulativeProbability999() {
  +        testValue(5.893, .999);
  +    }
  +    
  +    public void testInverseCumulativeProbability990() {
  +        testValue(3.365, .990);
  +    }
  +    
  +    public void testInverseCumulativeProbability975() {
  +        testValue(2.571, .975);
  +    }
  +
  +    public void testInverseCumulativeProbability950() {
  +        testValue(2.015, .950);
  +    }
  +    
  +    public void testInverseCumulativeProbability900() {
  +        testValue(1.476, .900);
  +    }
  +
  +    public void testCummulativeProbability001() {
           testProbability(-5.893, .001);
  +    }
  +    
  +    public void testCumulativeProbability010() {
           testProbability(-3.365, .010);
  +    }
  +    
  +    public void testCumulativeProbability025() {
           testProbability(-2.571, .025);
  +    }
  +
  +    public void testCumulativeProbability050() {
           testProbability(-2.015, .050);
  +    }
  +    
  +    public void testCumulativeProbability100() {
           testProbability(-1.476, .100);
       }
   
  -    public void testUpperTailProbability(){
  +    public void testCummulativeProbability999() {
           testProbability(5.893, .999);
  +    }
  +    
  +    public void testCumulativeProbability990() {
           testProbability(3.365, .990);
  -        testProbability(2.571, .975);
  -        testProbability(2.015, .950);
  -        testProbability(1.476, .900);
       }
       
  -    public void testLowerTailValues(){
  -        testValue(-5.893, .001);
  -        testValue(-3.365, .010);
  -        testValue(-2.571, .025);
  -        testValue(-2.015, .050);
  -        testValue(-1.476, .100);
  +    public void testCumulativeProbability975() {
  +        testProbability(2.571, .975);
  +    }
  +
  +    public void testCumulativeProbability950() {
  +        testProbability(2.015, .950);
       }
       
  -    public void testUpperTailValues(){
  -        testValue(5.893, .999);
  -        testValue(3.365, .990);
  -        testValue(2.571, .975);
  -        testValue(2.015, .950);
  -        testValue(1.476, .900);
  +    public void testCumulativeProbability900() {
  +        testProbability(1.476, .900);
       }
       
       private void testProbability(double x, double expected){
           double actual = t.cummulativeProbability(x);
  -        assertEquals("probability for " + x, expected, actual, 10e-4);
  +        assertEquals(expected, actual, 10e-4);
       }
       
       private void testValue(double expected, double p){
           double actual = t.inverseCummulativeProbability(p);
  -        assertEquals("value for " + p, expected, actual, 10e-4);
  +        assertEquals(expected, actual, 10e-4);
       }
   }
  
  
  
  1.1                  jakarta-commons-sandbox/math/src/test/org/apache/commons/math/special/BetaTest.java
  
  Index: BetaTest.java
  ===================================================================
  /* ====================================================================
   * The Apache Software License, Version 1.1
   *
   * Copyright (c) 2003 The Apache Software Foundation.  All rights
   * reserved.
   *
   * Redistribution and use in source and binary forms, with or without
   * modification, are permitted provided that the following conditions
   * are met:
   *
   * 1. Redistributions of source code must retain the above copyright
   *    notice, this list of conditions and the following disclaimer.
   *
   * 2. Redistributions in binary form must reproduce the above copyright
   *    notice, this list of conditions and the following disclaimer in
   *    the documentation and/or other materials provided with the
   *    distribution.
   *
   * 3. The end-user documentation included with the redistribution, if
   *    any, must include the following acknowlegement:
   *       "This product includes software developed by the
   *        Apache Software Foundation (http://www.apache.org/)."
   *    Alternately, this acknowlegement may appear in the software itself,
   *    if and wherever such third-party acknowlegements normally appear.
   *
   * 4. The names "The Jakarta Project", "Commons", and "Apache Software
   *    Foundation" must not be used to endorse or promote products derived
   *    from this software without prior written permission. For written
   *    permission, please contact apache@apache.org.
   *
   * 5. Products derived from this software may not be called "Apache"
   *    nor may "Apache" appear in their names without prior written
   *    permission of the Apache Software Foundation.
   *
   * THIS SOFTWARE IS PROVIDED ``AS IS'' AND ANY EXPRESSED OR IMPLIED
   * WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
   * OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
   * DISCLAIMED.  IN NO EVENT SHALL THE APACHE SOFTWARE FOUNDATION OR
   * ITS CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
   * SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
   * LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF
   * USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
   * ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
   * OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT
   * OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF
   * SUCH DAMAGE.
   * ====================================================================
   *
   * This software consists of voluntary contributions made by many
   * individuals on behalf of the Apache Software Foundation.  For more
   * information on the Apache Software Foundation, please see
   * <http://www.apache.org/>.
   */
  package org.apache.commons.math.special;
  
  import junit.framework.TestCase;
  
  /**
   * @author Brent Worden
   */
  public class BetaTest extends TestCase {
      /**
       * Constructor for BetaTest.
       * @param name
       */
      public BetaTest(String name) {
          super(name);
      }
  
      private void testRegularizedBeta(double expected, double x, double a, double b) {
          double actual = Beta.regularizedBeta(x, a, b);
          if (Double.isNaN(expected)) {
              assertTrue(Double.isNaN(actual));
          } else {
              assertEquals(expected, actual, 10e-5);
          }
      }
  
      private void testLogBeta(double expected, double a, double b) {
          double actual = Beta.logBeta(a, b);
          if (Double.isNaN(expected)) {
              assertTrue(Double.isNaN(actual));
          } else {
              assertEquals(expected, actual, 10e-5);
          }
      }
  
      public void testRegularizedBetaNanPositivePositive() {
          testRegularizedBeta(Double.NaN, Double.NaN, 1.0, 1.0);
      }
  
      public void testRegularizedBetaPositiveNanPositive() {
          testRegularizedBeta(Double.NaN, 0.5, Double.NaN, 1.0);
      }
  
      public void testRegularizedBetaPositivePositiveNan() {
          testRegularizedBeta(Double.NaN, 0.5, 1.0, Double.NaN);
      }
      
      public void testRegularizedBetaNegativePositivePositive() {
          testRegularizedBeta(Double.NaN, -0.5, 1.0, 2.0);
      }
      
      public void testRegularizedBetaPositiveNegativePositive() {
          testRegularizedBeta(Double.NaN, 0.5, -1.0, 2.0);
      }
      
      public void testRegularizedBetaPositivePositiveNegative() {
          testRegularizedBeta(Double.NaN, 0.5, 1.0, -2.0);
      }
      
      public void testRegularizedBetaZeroPositivePositive() {
          testRegularizedBeta(0.0, 0.0, 1.0, 2.0);
      }
      
      public void testRegularizedBetaPositiveZeroPositive() {
          testRegularizedBeta(Double.NaN, 0.5, 0.0, 2.0);
      }
      
      public void testRegularizedBetaPositivePositiveZero() {
          testRegularizedBeta(Double.NaN, 0.5, 1.0, 0.0);
      }
      
      public void testRegularizedBetaPositivePositivePositive() {
          testRegularizedBeta(0.75, 0.5, 1.0, 2.0);
      }
      
      public void testLogBetaNanPositive() {
          testLogBeta(Double.NaN, Double.NaN, 2.0);
      }
      
      public void testLogBetaPositiveNan() {
          testLogBeta(Double.NaN, 1.0, Double.NaN);
      }
      
      public void testLogBetaNegativePositive() {
          testLogBeta(Double.NaN, -1.0, 2.0);
      }
      
      public void testLogBetaPositiveNegative() {
          testLogBeta(Double.NaN, 1.0, -2.0);
      }
      
      public void testLogBetaZeroPositive() {
          testLogBeta(Double.NaN, 0.0, 2.0);
      }
      
      public void testLogBetaPositiveZero() {
          testLogBeta(Double.NaN, 1.0, 0.0);
      }
      
      public void testLogBetaPositivePositive() {
          testLogBeta(-0.693147, 1.0, 2.0);
      }
  }
  
  

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