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From pste...@apache.org
Subject svn commit: r811685 [10/24] - in /commons/proper/math/trunk: ./ src/main/java/org/apache/commons/math/ src/main/java/org/apache/commons/math/analysis/ src/main/java/org/apache/commons/math/analysis/integration/ src/main/java/org/apache/commons/math/ana...
Date Sat, 05 Sep 2009 17:37:05 GMT
Modified: commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/DescriptiveStatistics.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/DescriptiveStatistics.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/DescriptiveStatistics.java (original)
+++ commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/DescriptiveStatistics.java Sat Sep  5 17:36:48 2009
@@ -37,90 +37,90 @@
 /**
  * Maintains a dataset of values of a single variable and computes descriptive
  * statistics based on stored data. The {@link #getWindowSize() windowSize}
- * property sets a limit on the number of values that can be stored in the 
+ * property sets a limit on the number of values that can be stored in the
  * dataset.  The default value, INFINITE_WINDOW, puts no limit on the size of
  * the dataset.  This value should be used with caution, as the backing store
- * will grow without bound in this case.  For very large datasets, 
+ * will grow without bound in this case.  For very large datasets,
  * {@link SummaryStatistics}, which does not store the dataset, should be used
  * instead of this class. If <code>windowSize</code> is not INFINITE_WINDOW and
  * more values are added than can be stored in the dataset, new values are
- * added in a "rolling" manner, with new values replacing the "oldest" values 
+ * added in a "rolling" manner, with new values replacing the "oldest" values
  * in the dataset.
- * 
- * <p>Note: this class is not threadsafe.  Use 
+ *
+ * <p>Note: this class is not threadsafe.  Use
  * {@link SynchronizedDescriptiveStatistics} if concurrent access from multiple
  * threads is required.</p>
  *
  * @version $Revision$ $Date$
  */
 public class DescriptiveStatistics implements StatisticalSummary, Serializable {
-    
+
     /** Serialization UID */
     private static final long serialVersionUID = 4133067267405273064L;
 
     /** hold the window size **/
     protected int windowSize = INFINITE_WINDOW;
-    
-    /** 
+
+    /**
      *  Stored data values
      */
     protected ResizableDoubleArray eDA = new ResizableDoubleArray();
-  
+
     /** Mean statistic implementation - can be reset by setter. */
     private UnivariateStatistic meanImpl = new Mean();
-    
+
     /** Geometric mean statistic implementation - can be reset by setter. */
     private UnivariateStatistic geometricMeanImpl = new GeometricMean();
-    
+
     /** Kurtosis statistic implementation - can be reset by setter. */
     private UnivariateStatistic kurtosisImpl = new Kurtosis();
-    
+
     /** Maximum statistic implementation - can be reset by setter. */
     private UnivariateStatistic maxImpl = new Max();
-    
+
     /** Minimum statistic implementation - can be reset by setter. */
     private UnivariateStatistic minImpl = new Min();
-    
+
     /** Percentile statistic implementation - can be reset by setter. */
     private UnivariateStatistic percentileImpl = new Percentile();
-    
+
     /** Skewness statistic implementation - can be reset by setter. */
     private UnivariateStatistic skewnessImpl = new Skewness();
-    
+
     /** Variance statistic implementation - can be reset by setter. */
     private UnivariateStatistic varianceImpl = new Variance();
-    
+
     /** Sum of squares statistic implementation - can be reset by setter. */
     private UnivariateStatistic sumsqImpl = new SumOfSquares();
-    
+
     /** Sum statistic implementation - can be reset by setter. */
     private UnivariateStatistic sumImpl = new Sum();
-    
+
     /**
      * Construct a DescriptiveStatistics instance with an infinite window
      */
     public DescriptiveStatistics() {
     }
-    
+
     /**
      * Construct a DescriptiveStatistics instance with the specified window
-     * 
+     *
      * @param window the window size.
      */
     public DescriptiveStatistics(int window) {
         setWindowSize(window);
     }
-    
+
     /**
      * Copy constructor.  Construct a new DescriptiveStatistics instance that
      * is a copy of original.
-     * 
+     *
      * @param original DescriptiveStatistics instance to copy
      */
     public DescriptiveStatistics(DescriptiveStatistics original) {
         copy(original, this);
     }
-    
+
     /**
      * Represents an infinite window size.  When the {@link #getWindowSize()}
      * returns this value, there is no limit to the number of data values
@@ -133,8 +133,8 @@
      * (i.e., the number of stored elements equals the currently configured
      * windowSize), the first (oldest) element in the dataset is discarded
      * to make room for the new value.
-     * 
-     * @param v the value to be added 
+     *
+     * @param v the value to be added
      */
     public void addValue(double v) {
         if (windowSize != INFINITE_WINDOW) {
@@ -158,7 +158,7 @@
     /**
      * Replaces the most recently stored value with the given value.
      * There must be at least one element stored to call this method.
-     * 
+     *
      * @param v the value to replace the most recent stored value
      * @return replaced value
      */
@@ -166,38 +166,38 @@
         return eDA.substituteMostRecentElement(v);
     }
 
-    /** 
+    /**
      * Returns the <a href="http://www.xycoon.com/arithmetic_mean.htm">
-     * arithmetic mean </a> of the available values 
+     * arithmetic mean </a> of the available values
      * @return The mean or Double.NaN if no values have been added.
      */
     public double getMean() {
         return apply(meanImpl);
     }
 
-    /** 
+    /**
      * Returns the <a href="http://www.xycoon.com/geometric_mean.htm">
      * geometric mean </a> of the available values
-     * @return The geometricMean, Double.NaN if no values have been added, 
+     * @return The geometricMean, Double.NaN if no values have been added,
      * or if the product of the available values is less than or equal to 0.
      */
     public double getGeometricMean() {
         return apply(geometricMeanImpl);
     }
 
-    /** 
+    /**
      * Returns the variance of the available values.
-     * @return The variance, Double.NaN if no values have been added 
-     * or 0.0 for a single value set.  
+     * @return The variance, Double.NaN if no values have been added
+     * or 0.0 for a single value set.
      */
     public double getVariance() {
         return apply(varianceImpl);
     }
 
-    /** 
+    /**
      * Returns the standard deviation of the available values.
-     * @return The standard deviation, Double.NaN if no values have been added 
-     * or 0.0 for a single value set. 
+     * @return The standard deviation, Double.NaN if no values have been added
+     * or 0.0 for a single value set.
      */
     public double getStandardDeviation() {
         double stdDev = Double.NaN;
@@ -212,26 +212,26 @@
     }
 
     /**
-     * Returns the skewness of the available values. Skewness is a 
+     * Returns the skewness of the available values. Skewness is a
      * measure of the asymmetry of a given distribution.
-     * @return The skewness, Double.NaN if no values have been added 
-     * or 0.0 for a value set &lt;=2. 
+     * @return The skewness, Double.NaN if no values have been added
+     * or 0.0 for a value set &lt;=2.
      */
     public double getSkewness() {
         return apply(skewnessImpl);
     }
 
     /**
-     * Returns the Kurtosis of the available values. Kurtosis is a 
+     * Returns the Kurtosis of the available values. Kurtosis is a
      * measure of the "peakedness" of a distribution
-     * @return The kurtosis, Double.NaN if no values have been added, or 0.0 
-     * for a value set &lt;=3. 
+     * @return The kurtosis, Double.NaN if no values have been added, or 0.0
+     * for a value set &lt;=3.
      */
     public double getKurtosis() {
         return apply(kurtosisImpl);
     }
 
-    /** 
+    /**
      * Returns the maximum of the available values
      * @return The max or Double.NaN if no values have been added.
      */
@@ -239,7 +239,7 @@
         return apply(maxImpl);
     }
 
-    /** 
+    /**
     * Returns the minimum of the available values
     * @return The min or Double.NaN if no values have been added.
     */
@@ -247,7 +247,7 @@
         return apply(minImpl);
     }
 
-    /** 
+    /**
      * Returns the number of available values
      * @return The number of available values
      */
@@ -265,14 +265,14 @@
 
     /**
      * Returns the sum of the squares of the available values.
-     * @return The sum of the squares or Double.NaN if no 
+     * @return The sum of the squares or Double.NaN if no
      * values have been added.
      */
     public double getSumsq() {
         return apply(sumsqImpl);
     }
 
-    /** 
+    /**
      * Resets all statistics and storage
      */
     public void clear() {
@@ -283,7 +283,7 @@
     /**
      * Returns the maximum number of values that can be stored in the
      * dataset, or INFINITE_WINDOW (-1) if there is no limit.
-     * 
+     *
      * @return The current window size or -1 if its Infinite.
      */
     public int getWindowSize() {
@@ -291,10 +291,10 @@
     }
 
     /**
-     * WindowSize controls the number of values which contribute 
-     * to the reported statistics.  For example, if 
-     * windowSize is set to 3 and the values {1,2,3,4,5} 
-     * have been added <strong> in that order</strong> 
+     * WindowSize controls the number of values which contribute
+     * to the reported statistics.  For example, if
+     * windowSize is set to 3 and the values {1,2,3,4,5}
+     * have been added <strong> in that order</strong>
      * then the <i>available values</i> are {3,4,5} and all
      * reported statistics will be based on these values
      * @param windowSize sets the size of the window.
@@ -306,24 +306,24 @@
                       "window size must be positive ({0})", windowSize);
             }
         }
-        
+
         this.windowSize = windowSize;
 
         // We need to check to see if we need to discard elements
-        // from the front of the array.  If the windowSize is less than 
+        // from the front of the array.  If the windowSize is less than
         // the current number of elements.
         if (windowSize != INFINITE_WINDOW && windowSize < eDA.getNumElements()) {
             eDA.discardFrontElements(eDA.getNumElements() - windowSize);
         }
     }
-    
+
     /**
-     * Returns the current set of values in an array of double primitives.  
+     * Returns the current set of values in an array of double primitives.
      * The order of addition is preserved.  The returned array is a fresh
      * copy of the underlying data -- i.e., it is not a reference to the
      * stored data.
-     * 
-     * @return returns the current set of numbers in the order in which they 
+     *
+     * @return returns the current set of numbers in the order in which they
      *         were added to this set
      */
     public double[] getValues() {
@@ -331,12 +331,12 @@
     }
 
     /**
-     * Returns the current set of values in an array of double primitives,  
+     * Returns the current set of values in an array of double primitives,
      * sorted in ascending order.  The returned array is a fresh
      * copy of the underlying data -- i.e., it is not a reference to the
      * stored data.
-     * @return returns the current set of 
-     * numbers sorted in ascending order        
+     * @return returns the current set of
+     * numbers sorted in ascending order
      */
     public double[] getSortedValues() {
         double[] sort = getValues();
@@ -354,20 +354,20 @@
     }
 
     /**
-     * Returns an estimate for the pth percentile of the stored values. 
+     * Returns an estimate for the pth percentile of the stored values.
      * <p>
      * The implementation provided here follows the first estimation procedure presented
      * <a href="http://www.itl.nist.gov/div898/handbook/prc/section2/prc252.htm">here.</a>
      * </p><p>
      * <strong>Preconditions</strong>:<ul>
-     * <li><code>0 &lt; p &le; 100</code> (otherwise an 
+     * <li><code>0 &lt; p &le; 100</code> (otherwise an
      * <code>IllegalArgumentException</code> is thrown)</li>
      * <li>at least one value must be stored (returns <code>Double.NaN
      *     </code> otherwise)</li>
      * </ul></p>
-     * 
+     *
      * @param p the requested percentile (scaled from 0 - 100)
-     * @return An estimate for the pth percentile of the stored data 
+     * @return An estimate for the pth percentile of the stored data
      * @throws IllegalStateException if percentile implementation has been
      *  overridden and the supplied implementation does not support setQuantile
      * values
@@ -377,7 +377,7 @@
             ((Percentile) percentileImpl).setQuantile(p);
         } else {
             try {
-                percentileImpl.getClass().getMethod("setQuantile", 
+                percentileImpl.getClass().getMethod("setQuantile",
                         new Class[] {Double.TYPE}).invoke(percentileImpl,
                                 new Object[] {Double.valueOf(p)});
             } catch (NoSuchMethodException e1) { // Setter guard should prevent
@@ -389,17 +389,17 @@
                       "cannot access setQuantile method in percentile implementation {0}",
                       percentileImpl.getClass().getName());
             } catch (InvocationTargetException e3) {
-                throw MathRuntimeException.createIllegalArgumentException(e3.getCause()); 
+                throw MathRuntimeException.createIllegalArgumentException(e3.getCause());
             }
         }
         return apply(percentileImpl);
     }
-    
+
     /**
      * Generates a text report displaying univariate statistics from values
      * that have been added.  Each statistic is displayed on a separate
      * line.
-     * 
+     *
      * @return String with line feeds displaying statistics
      */
     @Override
@@ -418,7 +418,7 @@
         outBuffer.append("kurtosis: ").append(getKurtosis()).append(endl);
         return outBuffer.toString();
     }
-    
+
     /**
      * Apply the given statistic to the data associated with this set of statistics.
      * @param stat the statistic to apply
@@ -429,10 +429,10 @@
     }
 
     // Implementation getters and setter
-    
+
     /**
      * Returns the currently configured mean implementation.
-     * 
+     *
      * @return the UnivariateStatistic implementing the mean
      * @since 1.2
      */
@@ -442,7 +442,7 @@
 
     /**
      * <p>Sets the implementation for the mean.</p>
-     * 
+     *
      * @param meanImpl the UnivariateStatistic instance to use
      * for computing the mean
      * @since 1.2
@@ -453,7 +453,7 @@
 
     /**
      * Returns the currently configured geometric mean implementation.
-     * 
+     *
      * @return the UnivariateStatistic implementing the geometric mean
      * @since 1.2
      */
@@ -463,7 +463,7 @@
 
     /**
      * <p>Sets the implementation for the gemoetric mean.</p>
-     * 
+     *
      * @param geometricMeanImpl the UnivariateStatistic instance to use
      * for computing the geometric mean
      * @since 1.2
@@ -475,7 +475,7 @@
 
     /**
      * Returns the currently configured kurtosis implementation.
-     * 
+     *
      * @return the UnivariateStatistic implementing the kurtosis
      * @since 1.2
      */
@@ -485,7 +485,7 @@
 
     /**
      * <p>Sets the implementation for the kurtosis.</p>
-     * 
+     *
      * @param kurtosisImpl the UnivariateStatistic instance to use
      * for computing the kurtosis
      * @since 1.2
@@ -496,7 +496,7 @@
 
     /**
      * Returns the currently configured maximum implementation.
-     * 
+     *
      * @return the UnivariateStatistic implementing the maximum
      * @since 1.2
      */
@@ -506,7 +506,7 @@
 
     /**
      * <p>Sets the implementation for the maximum.</p>
-     * 
+     *
      * @param maxImpl the UnivariateStatistic instance to use
      * for computing the maximum
      * @since 1.2
@@ -517,7 +517,7 @@
 
     /**
      * Returns the currently configured minimum implementation.
-     * 
+     *
      * @return the UnivariateStatistic implementing the minimum
      * @since 1.2
      */
@@ -527,7 +527,7 @@
 
     /**
      * <p>Sets the implementation for the minimum.</p>
-     * 
+     *
      * @param minImpl the UnivariateStatistic instance to use
      * for computing the minimum
      * @since 1.2
@@ -538,7 +538,7 @@
 
     /**
      * Returns the currently configured percentile implementation.
-     * 
+     *
      * @return the UnivariateStatistic implementing the percentile
      * @since 1.2
      */
@@ -549,9 +549,9 @@
     /**
      * Sets the implementation to be used by {@link #getPercentile(double)}.
      * The supplied <code>UnivariateStatistic</code> must provide a
-     * <code>setQuantile(double)</code> method; otherwise 
+     * <code>setQuantile(double)</code> method; otherwise
      * <code>IllegalArgumentException</code> is thrown.
-     * 
+     *
      * @param percentileImpl the percentileImpl to set
      * @throws IllegalArgumentException if the supplied implementation does not
      *  provide a <code>setQuantile</code> method
@@ -560,10 +560,10 @@
     public synchronized void setPercentileImpl(
             UnivariateStatistic percentileImpl) {
         try {
-            percentileImpl.getClass().getMethod("setQuantile", 
+            percentileImpl.getClass().getMethod("setQuantile",
                     new Class[] {Double.TYPE}).invoke(percentileImpl,
                             new Object[] {Double.valueOf(50.0d)});
-        } catch (NoSuchMethodException e1) { 
+        } catch (NoSuchMethodException e1) {
             throw MathRuntimeException.createIllegalArgumentException(
                   "percentile implementation {0} does not support setQuantile",
                   percentileImpl.getClass().getName());
@@ -572,14 +572,14 @@
                   "cannot access setQuantile method in percentile implementation {0}",
                   percentileImpl.getClass().getName());
         } catch (InvocationTargetException e3) {
-            throw MathRuntimeException.createIllegalArgumentException(e3.getCause()); 
+            throw MathRuntimeException.createIllegalArgumentException(e3.getCause());
         }
         this.percentileImpl = percentileImpl;
     }
 
     /**
      * Returns the currently configured skewness implementation.
-     * 
+     *
      * @return the UnivariateStatistic implementing the skewness
      * @since 1.2
      */
@@ -589,7 +589,7 @@
 
     /**
      * <p>Sets the implementation for the skewness.</p>
-     * 
+     *
      * @param skewnessImpl the UnivariateStatistic instance to use
      * for computing the skewness
      * @since 1.2
@@ -601,7 +601,7 @@
 
     /**
      * Returns the currently configured variance implementation.
-     * 
+     *
      * @return the UnivariateStatistic implementing the variance
      * @since 1.2
      */
@@ -611,7 +611,7 @@
 
     /**
      * <p>Sets the implementation for the variance.</p>
-     * 
+     *
      * @param varianceImpl the UnivariateStatistic instance to use
      * for computing the variance
      * @since 1.2
@@ -623,7 +623,7 @@
 
     /**
      * Returns the currently configured sum of squares implementation.
-     * 
+     *
      * @return the UnivariateStatistic implementing the sum of squares
      * @since 1.2
      */
@@ -633,7 +633,7 @@
 
     /**
      * <p>Sets the implementation for the sum of squares.</p>
-     * 
+     *
      * @param sumsqImpl the UnivariateStatistic instance to use
      * for computing the sum of squares
      * @since 1.2
@@ -644,7 +644,7 @@
 
     /**
      * Returns the currently configured sum implementation.
-     * 
+     *
      * @return the UnivariateStatistic implementing the sum
      * @since 1.2
      */
@@ -654,30 +654,30 @@
 
     /**
      * <p>Sets the implementation for the sum.</p>
-     * 
+     *
      * @param sumImpl the UnivariateStatistic instance to use
      * for computing the sum
      * @since 1.2
      */
     public synchronized void setSumImpl(UnivariateStatistic sumImpl) {
         this.sumImpl = sumImpl;
-    }  
-    
+    }
+
     /**
      * Returns a copy of this DescriptiveStatistics instance with the same internal state.
-     * 
+     *
      * @return a copy of this
      */
     public DescriptiveStatistics copy() {
         DescriptiveStatistics result = new DescriptiveStatistics();
         copy(this, result);
-        return result; 
+        return result;
     }
-     
+
     /**
      * Copies source to dest.
      * <p>Neither source nor dest can be null.</p>
-     * 
+     *
      * @param source DescriptiveStatistics to copy
      * @param dest DescriptiveStatistics to copy to
      * @throws NullPointerException if either source or dest is null
@@ -686,7 +686,7 @@
         // Copy data and window size
         dest.eDA = source.eDA.copy();
         dest.windowSize = source.windowSize;
-        
+
         // Copy implementations
         dest.maxImpl = source.maxImpl.copy();
         dest.meanImpl = source.meanImpl.copy();

Modified: commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/MultivariateSummaryStatistics.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/MultivariateSummaryStatistics.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/MultivariateSummaryStatistics.java (original)
+++ commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/MultivariateSummaryStatistics.java Sat Sep  5 17:36:48 2009
@@ -33,22 +33,22 @@
 import org.apache.commons.math.util.MathUtils;
 
 /**
- * <p>Computes summary statistics for a stream of n-tuples added using the 
+ * <p>Computes summary statistics for a stream of n-tuples added using the
  * {@link #addValue(double[]) addValue} method. The data values are not stored
  * in memory, so this class can be used to compute statistics for very large
  * n-tuple streams.</p>
- * 
+ *
  * <p>The {@link StorelessUnivariateStatistic} instances used to maintain
  * summary state and compute statistics are configurable via setters.
  * For example, the default implementation for the mean can be overridden by
  * calling {@link #setMeanImpl(StorelessUnivariateStatistic[])}. Actual
- * parameters to these methods must implement the 
+ * parameters to these methods must implement the
  * {@link StorelessUnivariateStatistic} interface and configuration must be
  * completed before <code>addValue</code> is called. No configuration is
  * necessary to use the default, commons-math provided implementations.</p>
- * 
+ *
  * <p>To compute statistics for a stream of n-tuples, construct a
- * MultivariateStatistics instance with dimension n and then use 
+ * MultivariateStatistics instance with dimension n and then use
  * {@link #addValue(double[])} to add n-tuples. The <code>getXxx</code>
  * methods where Xxx is a statistic return an array of <code>double</code>
  * values, where for <code>i = 0,...,n-1</code> the i<sup>th</sup> array element is the
@@ -57,8 +57,8 @@
  * with actual parameters {0, 1, 2}, then {3, 4, 5} and finally {6, 7, 8},
  * <code>getSum</code> will return a three-element array with values
  * {0+3+6, 1+4+7, 2+5+8}</p>
- * 
- * <p>Note: This class is not thread-safe. Use 
+ *
+ * <p>Note: This class is not thread-safe. Use
  * {@link SynchronizedMultivariateSummaryStatistics} if concurrent access from multiple
  * threads is required.</p>
  *
@@ -109,34 +109,34 @@
 
     /** Count of values that have been added */
     private long n = 0;
-    
+
     /** Sum statistic implementation - can be reset by setter. */
     private StorelessUnivariateStatistic[] sumImpl;
-    
+
     /** Sum of squares statistic implementation - can be reset by setter. */
     private StorelessUnivariateStatistic[] sumSqImpl;
-    
+
     /** Minimum statistic implementation - can be reset by setter. */
     private StorelessUnivariateStatistic[] minImpl;
-    
+
     /** Maximum statistic implementation - can be reset by setter. */
     private StorelessUnivariateStatistic[] maxImpl;
-    
+
     /** Sum of log statistic implementation - can be reset by setter. */
     private StorelessUnivariateStatistic[] sumLogImpl;
-    
+
     /** Geometric mean statistic implementation - can be reset by setter. */
     private StorelessUnivariateStatistic[] geoMeanImpl;
-    
+
     /** Mean statistic implementation - can be reset by setter. */
     private StorelessUnivariateStatistic[] meanImpl;
-    
+
     /** Covariance statistic implementation - cannot be reset. */
     private VectorialCovariance covarianceImpl;
 
     /**
      * Add an n-tuple to the data
-     * 
+     *
      * @param value  the n-tuple to add
      * @throws DimensionMismatchException if the length of the array
      * does not match the one used at construction
@@ -158,7 +158,7 @@
         n++;
     }
 
-    /** 
+    /**
      * Returns the dimension of the data
      * @return The dimension of the data
      */
@@ -166,7 +166,7 @@
         return k;
     }
 
-    /** 
+    /**
      * Returns the number of available values
      * @return The number of available values
      */
@@ -189,9 +189,9 @@
 
     /**
      * Returns an array whose i<sup>th</sup> entry is the sum of the
-     * i<sup>th</sup> entries of the arrays that have been added using 
+     * i<sup>th</sup> entries of the arrays that have been added using
      * {@link #addValue(double[])}
-     * 
+     *
      * @return the array of component sums
      */
     public double[] getSum() {
@@ -200,9 +200,9 @@
 
     /**
      * Returns an array whose i<sup>th</sup> entry is the sum of squares of the
-     * i<sup>th</sup> entries of the arrays that have been added using 
+     * i<sup>th</sup> entries of the arrays that have been added using
      * {@link #addValue(double[])}
-     * 
+     *
      * @return the array of component sums of squares
      */
     public double[] getSumSq() {
@@ -211,9 +211,9 @@
 
     /**
      * Returns an array whose i<sup>th</sup> entry is the sum of logs of the
-     * i<sup>th</sup> entries of the arrays that have been added using 
+     * i<sup>th</sup> entries of the arrays that have been added using
      * {@link #addValue(double[])}
-     * 
+     *
      * @return the array of component log sums
      */
     public double[] getSumLog() {
@@ -222,9 +222,9 @@
 
     /**
      * Returns an array whose i<sup>th</sup> entry is the mean of the
-     * i<sup>th</sup> entries of the arrays that have been added using 
+     * i<sup>th</sup> entries of the arrays that have been added using
      * {@link #addValue(double[])}
-     * 
+     *
      * @return the array of component means
      */
     public double[] getMean() {
@@ -233,9 +233,9 @@
 
     /**
      * Returns an array whose i<sup>th</sup> entry is the standard deviation of the
-     * i<sup>th</sup> entries of the arrays that have been added using 
+     * i<sup>th</sup> entries of the arrays that have been added using
      * {@link #addValue(double[])}
-     * 
+     *
      * @return the array of component standard deviations
      */
     public double[] getStandardDeviation() {
@@ -256,7 +256,7 @@
     /**
      * Returns the covariance matrix of the values that have been added.
      *
-     * @return the covariance matrix 
+     * @return the covariance matrix
      */
     public RealMatrix getCovariance() {
         return covarianceImpl.getResult();
@@ -264,9 +264,9 @@
 
     /**
      * Returns an array whose i<sup>th</sup> entry is the maximum of the
-     * i<sup>th</sup> entries of the arrays that have been added using 
+     * i<sup>th</sup> entries of the arrays that have been added using
      * {@link #addValue(double[])}
-     * 
+     *
      * @return the array of component maxima
      */
     public double[] getMax() {
@@ -275,9 +275,9 @@
 
     /**
      * Returns an array whose i<sup>th</sup> entry is the minimum of the
-     * i<sup>th</sup> entries of the arrays that have been added using 
+     * i<sup>th</sup> entries of the arrays that have been added using
      * {@link #addValue(double[])}
-     * 
+     *
      * @return the array of component minima
      */
     public double[] getMin() {
@@ -286,15 +286,15 @@
 
     /**
      * Returns an array whose i<sup>th</sup> entry is the geometric mean of the
-     * i<sup>th</sup> entries of the arrays that have been added using 
+     * i<sup>th</sup> entries of the arrays that have been added using
      * {@link #addValue(double[])}
-     * 
+     *
      * @return the array of component geometric means
      */
     public double[] getGeometricMean() {
         return getResults(geoMeanImpl);
     }
-    
+
     /**
      * Generates a text report displaying
      * summary statistics from values that
@@ -337,7 +337,7 @@
         buffer.append(suffix);
     }
 
-    /** 
+    /**
      * Resets all statistics and storage
      */
     public void clear() {
@@ -353,7 +353,7 @@
         }
         covarianceImpl.clear();
     }
-    
+
     /**
      * Returns true iff <code>object</code> is a <code>SummaryStatistics</code>
      * instance and all statistics have the same values as this.
@@ -369,9 +369,9 @@
             return false;
         }
         MultivariateSummaryStatistics stat = (MultivariateSummaryStatistics) object;
-        return (MathUtils.equals(stat.getGeometricMean(), 
+        return (MathUtils.equals(stat.getGeometricMean(),
                 this.getGeometricMean()) &&
-                MathUtils.equals(stat.getMax(), this.getMax()) && 
+                MathUtils.equals(stat.getMax(), this.getMax()) &&
                 MathUtils.equals(stat.getMean(),this.getMean()) &&
                 MathUtils.equals(stat.getMin(),this.getMin()) &&
                 MathUtils.equals(stat.getN(), this.getN()) &&
@@ -380,10 +380,10 @@
                 MathUtils.equals(stat.getSumLog(),this.getSumLog()) &&
                 stat.getCovariance().equals(this.getCovariance()));
     }
-    
+
     /**
      * Returns hash code based on values of statistics
-     * 
+     *
      * @return hash code
      */
     @Override
@@ -421,7 +421,7 @@
 
     /**
      * Returns the currently configured Sum implementation
-     * 
+     *
      * @return the StorelessUnivariateStatistic implementing the sum
      */
     public StorelessUnivariateStatistic[] getSumImpl() {
@@ -431,9 +431,9 @@
     /**
      * <p>Sets the implementation for the Sum.</p>
      * <p>This method must be activated before any data has been added - i.e.,
-     * before {@link #addValue(double[]) addValue} has been used to add data; 
+     * before {@link #addValue(double[]) addValue} has been used to add data;
      * otherwise an IllegalStateException will be thrown.</p>
-     * 
+     *
      * @param sumImpl the StorelessUnivariateStatistic instance to use
      * for computing the Sum
      * @throws DimensionMismatchException if the array dimension
@@ -448,7 +448,7 @@
 
     /**
      * Returns the currently configured sum of squares implementation
-     * 
+     *
      * @return the StorelessUnivariateStatistic implementing the sum of squares
      */
     public StorelessUnivariateStatistic[] getSumsqImpl() {
@@ -458,9 +458,9 @@
     /**
      * <p>Sets the implementation for the sum of squares.</p>
      * <p>This method must be activated before any data has been added - i.e.,
-     * before {@link #addValue(double[]) addValue} has been used to add data; 
+     * before {@link #addValue(double[]) addValue} has been used to add data;
      * otherwise an IllegalStateException will be thrown.</p>
-     * 
+     *
      * @param sumsqImpl the StorelessUnivariateStatistic instance to use
      * for computing the sum of squares
      * @throws DimensionMismatchException if the array dimension
@@ -475,7 +475,7 @@
 
     /**
      * Returns the currently configured minimum implementation
-     * 
+     *
      * @return the StorelessUnivariateStatistic implementing the minimum
      */
     public StorelessUnivariateStatistic[] getMinImpl() {
@@ -485,9 +485,9 @@
     /**
      * <p>Sets the implementation for the minimum.</p>
      * <p>This method must be activated before any data has been added - i.e.,
-     * before {@link #addValue(double[]) addValue} has been used to add data; 
+     * before {@link #addValue(double[]) addValue} has been used to add data;
      * otherwise an IllegalStateException will be thrown.</p>
-     * 
+     *
      * @param minImpl the StorelessUnivariateStatistic instance to use
      * for computing the minimum
      * @throws DimensionMismatchException if the array dimension
@@ -502,7 +502,7 @@
 
     /**
      * Returns the currently configured maximum implementation
-     * 
+     *
      * @return the StorelessUnivariateStatistic implementing the maximum
      */
     public StorelessUnivariateStatistic[] getMaxImpl() {
@@ -512,9 +512,9 @@
     /**
      * <p>Sets the implementation for the maximum.</p>
      * <p>This method must be activated before any data has been added - i.e.,
-     * before {@link #addValue(double[]) addValue} has been used to add data; 
+     * before {@link #addValue(double[]) addValue} has been used to add data;
      * otherwise an IllegalStateException will be thrown.</p>
-     * 
+     *
      * @param maxImpl the StorelessUnivariateStatistic instance to use
      * for computing the maximum
      * @throws DimensionMismatchException if the array dimension
@@ -529,7 +529,7 @@
 
     /**
      * Returns the currently configured sum of logs implementation
-     * 
+     *
      * @return the StorelessUnivariateStatistic implementing the log sum
      */
     public StorelessUnivariateStatistic[] getSumLogImpl() {
@@ -539,14 +539,14 @@
     /**
      * <p>Sets the implementation for the sum of logs.</p>
      * <p>This method must be activated before any data has been added - i.e.,
-     * before {@link #addValue(double[]) addValue} has been used to add data; 
+     * before {@link #addValue(double[]) addValue} has been used to add data;
      * otherwise an IllegalStateException will be thrown.</p>
-     * 
+     *
      * @param sumLogImpl the StorelessUnivariateStatistic instance to use
      * for computing the log sum
      * @throws DimensionMismatchException if the array dimension
      * does not match the one used at construction
-     * @throws IllegalStateException if data has already been added 
+     * @throws IllegalStateException if data has already been added
      *  (i.e if n > 0)
      */
     public void setSumLogImpl(StorelessUnivariateStatistic[] sumLogImpl)
@@ -556,7 +556,7 @@
 
     /**
      * Returns the currently configured geometric mean implementation
-     * 
+     *
      * @return the StorelessUnivariateStatistic implementing the geometric mean
      */
     public StorelessUnivariateStatistic[] getGeoMeanImpl() {
@@ -566,9 +566,9 @@
     /**
      * <p>Sets the implementation for the geometric mean.</p>
      * <p>This method must be activated before any data has been added - i.e.,
-     * before {@link #addValue(double[]) addValue} has been used to add data; 
+     * before {@link #addValue(double[]) addValue} has been used to add data;
      * otherwise an IllegalStateException will be thrown.</p>
-     * 
+     *
      * @param geoMeanImpl the StorelessUnivariateStatistic instance to use
      * for computing the geometric mean
      * @throws DimensionMismatchException if the array dimension
@@ -583,7 +583,7 @@
 
     /**
      * Returns the currently configured mean implementation
-     * 
+     *
      * @return the StorelessUnivariateStatistic implementing the mean
      */
     public StorelessUnivariateStatistic[] getMeanImpl() {
@@ -593,9 +593,9 @@
     /**
      * <p>Sets the implementation for the mean.</p>
      * <p>This method must be activated before any data has been added - i.e.,
-     * before {@link #addValue(double[]) addValue} has been used to add data; 
+     * before {@link #addValue(double[]) addValue} has been used to add data;
      * otherwise an IllegalStateException will be thrown.</p>
-     * 
+     *
      * @param meanImpl the StorelessUnivariateStatistic instance to use
      * for computing the mean
      * @throws DimensionMismatchException if the array dimension

Modified: commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/StatisticalMultivariateSummary.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/StatisticalMultivariateSummary.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/StatisticalMultivariateSummary.java (original)
+++ commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/StatisticalMultivariateSummary.java Sat Sep  5 17:36:48 2009
@@ -25,7 +25,7 @@
  * @version $Revision$ $Date$
  */
 public interface StatisticalMultivariateSummary {
-    /** 
+    /**
      * Returns the dimension of the data
      * @return The dimension of the data
      */
@@ -34,21 +34,21 @@
      * Returns an array whose i<sup>th</sup> entry is the
      * mean of the i<sup>th</sup> entries of the arrays
      * that correspond to each multivariate sample
-     * 
+     *
      * @return the array of component means
      */
     public abstract double[] getMean();
-    /** 
+    /**
      * Returns the covariance of the available values.
      * @return The covariance, null if no multivariate sample
-     * have been added or a zeroed matrix for a single value set.  
+     * have been added or a zeroed matrix for a single value set.
      */
     public abstract RealMatrix getCovariance();
     /**
      * Returns an array whose i<sup>th</sup> entry is the
      * standard deviation of the i<sup>th</sup> entries of the arrays
      * that correspond to each multivariate sample
-     * 
+     *
      * @return the array of component standard deviations
      */
     public abstract double[] getStandardDeviation();
@@ -56,7 +56,7 @@
      * Returns an array whose i<sup>th</sup> entry is the
      * maximum of the i<sup>th</sup> entries of the arrays
      * that correspond to each multivariate sample
-     * 
+     *
      * @return the array of component maxima
      */
     public abstract double[] getMax();
@@ -64,11 +64,11 @@
      * Returns an array whose i<sup>th</sup> entry is the
      * minimum of the i<sup>th</sup> entries of the arrays
      * that correspond to each multivariate sample
-     * 
+     *
      * @return the array of component minima
      */
     public abstract double[] getMin();
-    /** 
+    /**
      * Returns the number of available values
      * @return The number of available values
      */
@@ -77,7 +77,7 @@
      * Returns an array whose i<sup>th</sup> entry is the
      * geometric mean of the i<sup>th</sup> entries of the arrays
      * that correspond to each multivariate sample
-     * 
+     *
      * @return the array of component geometric means
      */
     public double[] getGeometricMean();
@@ -85,7 +85,7 @@
      * Returns an array whose i<sup>th</sup> entry is the
      * sum of the i<sup>th</sup> entries of the arrays
      * that correspond to each multivariate sample
-     * 
+     *
      * @return the array of component sums
      */
     public abstract double[] getSum();
@@ -93,7 +93,7 @@
      * Returns an array whose i<sup>th</sup> entry is the
      * sum of squares of the i<sup>th</sup> entries of the arrays
      * that correspond to each multivariate sample
-     * 
+     *
      * @return the array of component sums of squares
      */
     public abstract double[] getSumSq();
@@ -101,8 +101,8 @@
      * Returns an array whose i<sup>th</sup> entry is the
      * sum of logs of the i<sup>th</sup> entries of the arrays
      * that correspond to each multivariate sample
-     * 
+     *
      * @return the array of component log sums
      */
     public abstract double[] getSumLog();
-}
\ No newline at end of file
+}

Modified: commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/StatisticalSummary.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/StatisticalSummary.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/StatisticalSummary.java (original)
+++ commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/StatisticalSummary.java Sat Sep  5 17:36:48 2009
@@ -22,35 +22,35 @@
   * @version $Revision$ $Date$
  */
 public interface StatisticalSummary {
-    /** 
+    /**
      * Returns the <a href="http://www.xycoon.com/arithmetic_mean.htm">
-     * arithmetic mean </a> of the available values 
+     * arithmetic mean </a> of the available values
      * @return The mean or Double.NaN if no values have been added.
      */
     public abstract double getMean();
-    /** 
+    /**
      * Returns the variance of the available values.
-     * @return The variance, Double.NaN if no values have been added 
-     * or 0.0 for a single value set.  
+     * @return The variance, Double.NaN if no values have been added
+     * or 0.0 for a single value set.
      */
     public abstract double getVariance();
-    /** 
+    /**
      * Returns the standard deviation of the available values.
-     * @return The standard deviation, Double.NaN if no values have been added 
-     * or 0.0 for a single value set. 
+     * @return The standard deviation, Double.NaN if no values have been added
+     * or 0.0 for a single value set.
      */
     public abstract double getStandardDeviation();
-    /** 
+    /**
      * Returns the maximum of the available values
      * @return The max or Double.NaN if no values have been added.
      */
     public abstract double getMax();
-    /** 
+    /**
     * Returns the minimum of the available values
     * @return The min or Double.NaN if no values have been added.
     */
     public abstract double getMin();
-    /** 
+    /**
      * Returns the number of available values
      * @return The number of available values
      */
@@ -60,4 +60,4 @@
      * @return The sum or Double.NaN if no values have been added
      */
     public abstract double getSum();
-}
\ No newline at end of file
+}

Modified: commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/StatisticalSummaryValues.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/StatisticalSummaryValues.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/StatisticalSummaryValues.java (original)
+++ commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/StatisticalSummaryValues.java Sat Sep  5 17:36:48 2009
@@ -24,36 +24,36 @@
  *
  * @version $Revision$ $Date$
  */
-public class StatisticalSummaryValues implements Serializable, 
+public class StatisticalSummaryValues implements Serializable,
     StatisticalSummary {
-   
+
     /** Serialization id */
     private static final long serialVersionUID = -5108854841843722536L;
 
     /** The sample mean */
     private final double mean;
-    
+
     /** The sample variance */
     private final double variance;
-    
+
     /** The number of observations in the sample */
     private final long n;
-    
+
     /** The maximum value */
     private final double max;
-    
+
     /** The minimum value */
     private final double min;
-    
+
     /** The sum of the sample values */
     private final double sum;
-    
+
     /**
       * Constructor
-      * 
+      *
       * @param mean  the sample mean
       * @param variance  the sample variance
-      * @param n  the number of observations in the sample 
+      * @param n  the number of observations in the sample
       * @param max  the maximum value
       * @param min  the minimum value
       * @param sum  the sum of the values
@@ -103,7 +103,7 @@
     public double getSum() {
         return sum;
     }
-    
+
     /**
      * @return Returns the standard deviation
      */
@@ -117,12 +117,12 @@
     public double getVariance() {
         return variance;
     }
-    
+
     /**
-     * Returns true iff <code>object</code> is a 
+     * Returns true iff <code>object</code> is a
      * <code>StatisticalSummaryValues</code> instance and all statistics have
      *  the same values as this.
-     * 
+     *
      * @param object the object to test equality against.
      * @return true if object equals this
      */
@@ -135,17 +135,17 @@
             return false;
         }
         StatisticalSummaryValues stat = (StatisticalSummaryValues) object;
-        return (MathUtils.equals(stat.getMax(), this.getMax()) && 
+        return (MathUtils.equals(stat.getMax(), this.getMax()) &&
                 MathUtils.equals(stat.getMean(),this.getMean()) &&
                 MathUtils.equals(stat.getMin(),this.getMin()) &&
                 MathUtils.equals(stat.getN(), this.getN()) &&
                 MathUtils.equals(stat.getSum(), this.getSum()) &&
                 MathUtils.equals(stat.getVariance(),this.getVariance()));
     }
-    
+
     /**
      * Returns hash code based on values of statistics
-     * 
+     *
      * @return hash code
      */
     @Override

Modified: commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/StorelessUnivariateStatistic.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/StorelessUnivariateStatistic.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/StorelessUnivariateStatistic.java (original)
+++ commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/StorelessUnivariateStatistic.java Sat Sep  5 17:36:48 2009
@@ -17,9 +17,9 @@
 package org.apache.commons.math.stat.descriptive;
 
 /**
- * Extends the definition of {@link UnivariateStatistic} with 
+ * Extends the definition of {@link UnivariateStatistic} with
  * {@link #increment} and {@link #incrementAll(double[])} methods for adding
- * values and updating internal state.  
+ * values and updating internal state.
  * <p>
  * This interface is designed to be used for calculating statistics that can be
  * computed in one pass through the data without storing the full array of
@@ -34,23 +34,23 @@
      * @param d  the new value.
      */
     void increment(double d);
-    
+
     /**
      * Updates the internal state of the statistic to reflect addition of
      * all values in the values array.  Does not clear the statistic first --
      * i.e., the values are added <strong>incrementally</strong> to the dataset.
-     * 
+     *
      * @param values  array holding the new values to add
      * @throws IllegalArgumentException if the array is null
      */
     void incrementAll(double[] values);
-    
+
     /**
      * Updates the internal state of the statistic to reflect addition of
      * the values in the designated portion of the values array.  Does not
-     * clear the statistic first -- i.e., the values are added 
+     * clear the statistic first -- i.e., the values are added
      * <strong>incrementally</strong> to the dataset.
-     * 
+     *
      * @param values  array holding the new values to add
      * @param start  the array index of the first value to add
      * @param length  the number of elements to add
@@ -75,12 +75,12 @@
      * Clears the internal state of the Statistic
      */
     void clear();
-    
+
     /**
      * Returns a copy of the statistic with the same internal state.
-     * 
+     *
      * @return a copy of the statistic
      */
     StorelessUnivariateStatistic copy();
 
-}
\ No newline at end of file
+}

Modified: commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/SummaryStatistics.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/SummaryStatistics.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/SummaryStatistics.java (original)
+++ commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/SummaryStatistics.java Sat Sep  5 17:36:48 2009
@@ -67,7 +67,7 @@
 
     /**
      * A copy constructor. Creates a deep-copy of the {@code original}.
-     * 
+     *
      * @param original the {@code SummaryStatistics} instance to copy
      */
     public SummaryStatistics(SummaryStatistics original) {
@@ -134,7 +134,7 @@
      * @return Current values of statistics
      */
     public StatisticalSummary getSummary() {
-        return new StatisticalSummaryValues(getMean(), getVariance(), getN(), 
+        return new StatisticalSummaryValues(getMean(), getVariance(), getN(),
                 getMax(), getMin(), getSum());
     }
 
@@ -283,7 +283,7 @@
     public double getSumOfLogs() {
         return sumLogImpl.getResult();
     }
-    
+
     /**
      * Returns a statistic related to the Second Central Moment.  Specifically,
      * what is returned is the sum of squared deviations from the sample mean
@@ -633,22 +633,22 @@
                     n);
         }
     }
-    
+
     /**
      * Returns a copy of this SummaryStatistics instance with the same internal state.
-     * 
+     *
      * @return a copy of this
      */
     public SummaryStatistics copy() {
         SummaryStatistics result = new SummaryStatistics();
         copy(this, result);
-        return result; 
+        return result;
     }
-     
+
     /**
      * Copies source to dest.
      * <p>Neither source nor dest can be null.</p>
-     * 
+     *
      * @param source SummaryStatistics to copy
      * @param dest SummaryStatistics to copy to
      * @throws NullPointerException if either source or dest is null
@@ -669,48 +669,48 @@
         }
         SecondMoment.copy(source.secondMoment, dest.secondMoment);
         dest.n = source.n;
-        
+
         // Make sure that if stat == statImpl in source, same
         // holds in dest; otherwise copy stat
         if (source.geoMean == source.geoMeanImpl) {
             dest.geoMean = (GeometricMean) dest.geoMeanImpl;
         } else {
             GeometricMean.copy(source.geoMean, dest.geoMean);
-        } 
+        }
         if (source.max == source.maxImpl) {
             dest.max = (Max) dest.maxImpl;
         } else {
             Max.copy(source.max, dest.max);
-        } 
+        }
         if (source.mean == source.meanImpl) {
             dest.mean = (Mean) dest.meanImpl;
         } else {
             Mean.copy(source.mean, dest.mean);
-        } 
+        }
         if (source.min == source.minImpl) {
             dest.min = (Min) dest.minImpl;
         } else {
             Min.copy(source.min, dest.min);
-        } 
+        }
         if (source.sum == source.sumImpl) {
             dest.sum = (Sum) dest.sumImpl;
         } else {
             Sum.copy(source.sum, dest.sum);
-        } 
+        }
         if (source.variance == source.varianceImpl) {
             dest.variance = (Variance) dest.varianceImpl;
         } else {
             Variance.copy(source.variance, dest.variance);
-        } 
+        }
         if (source.sumLog == source.sumLogImpl) {
             dest.sumLog = (SumOfLogs) dest.sumLogImpl;
         } else {
             SumOfLogs.copy(source.sumLog, dest.sumLog);
-        } 
+        }
         if (source.sumsq == source.sumsqImpl) {
             dest.sumsq = (SumOfSquares) dest.sumsqImpl;
         } else {
             SumOfSquares.copy(source.sumsq, dest.sumsq);
-        } 
+        }
     }
 }

Modified: commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/SynchronizedDescriptiveStatistics.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/SynchronizedDescriptiveStatistics.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/SynchronizedDescriptiveStatistics.java (original)
+++ commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/SynchronizedDescriptiveStatistics.java Sat Sep  5 17:36:48 2009
@@ -24,7 +24,7 @@
  * conditions.  In effect, this implementation makes modification and access
  * methods atomic operations for a single instance.  That is to say, as one
  * thread is computing a statistic from the instance, no other thread can modify
- * the instance nor compute another statistic. 
+ * the instance nor compute another statistic.
  *
  * @since 1.2
  * @version $Revision$ $Date$
@@ -48,10 +48,10 @@
     public SynchronizedDescriptiveStatistics(int window) {
         super(window);
     }
-    
+
     /**
      * A copy constructor. Creates a deep-copy of the {@code original}.
-     * 
+     *
      * @param original the {@code SynchronizedDescriptiveStatistics} instance to copy
      */
     public SynchronizedDescriptiveStatistics(SynchronizedDescriptiveStatistics original) {
@@ -98,7 +98,7 @@
         return super.getN();
     }
 
-    /** 
+    /**
      * {@inheritDoc}
      */
     @Override
@@ -137,26 +137,26 @@
     public synchronized String toString() {
         return super.toString();
     }
-    
+
     /**
      * Returns a copy of this SynchronizedDescriptiveStatistics instance with the
      * same internal state.
-     * 
+     *
      * @return a copy of this
      */
     @Override
     public synchronized SynchronizedDescriptiveStatistics copy() {
-        SynchronizedDescriptiveStatistics result = 
+        SynchronizedDescriptiveStatistics result =
             new SynchronizedDescriptiveStatistics();
         copy(this, result);
-        return result; 
+        return result;
     }
-     
+
     /**
      * Copies source to dest.
      * <p>Neither source nor dest can be null.</p>
      * <p>Acquires synchronization lock on source, then dest before copying.</p>
-     * 
+     *
      * @param source SynchronizedDescriptiveStatistics to copy
      * @param dest SynchronizedDescriptiveStatistics to copy to
      * @throws NullPointerException if either source or dest is null

Modified: commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/SynchronizedMultivariateSummaryStatistics.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/SynchronizedMultivariateSummaryStatistics.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/SynchronizedMultivariateSummaryStatistics.java (original)
+++ commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/SynchronizedMultivariateSummaryStatistics.java Sat Sep  5 17:36:48 2009
@@ -144,7 +144,7 @@
     public synchronized double[] getGeometricMean() {
         return super.getGeometricMean();
     }
-    
+
     /**
      * {@inheritDoc}
      */
@@ -160,7 +160,7 @@
     public synchronized void clear() {
         super.clear();
     }
-    
+
     /**
      * {@inheritDoc}
      */
@@ -168,7 +168,7 @@
     public synchronized boolean equals(Object object) {
         return super.equals(object);
     }
-    
+
     /**
      * {@inheritDoc}
      */

Modified: commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/SynchronizedSummaryStatistics.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/SynchronizedSummaryStatistics.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/SynchronizedSummaryStatistics.java (original)
+++ commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/SynchronizedSummaryStatistics.java Sat Sep  5 17:36:48 2009
@@ -24,7 +24,7 @@
  * conditions.  In effect, this implementation makes modification and access
  * methods atomic operations for a single instance.  That is to say, as one
  * thread is computing a statistic from the instance, no other thread can modify
- * the instance nor compute another statistic. 
+ * the instance nor compute another statistic.
  *
  * @since 1.2
  * @version $Revision$ $Date$
@@ -40,10 +40,10 @@
     public SynchronizedSummaryStatistics() {
         super();
     }
-    
+
     /**
      * A copy constructor. Creates a deep-copy of the {@code original}.
-     * 
+     *
      * @param original the {@code SynchronizedSummaryStatistics} instance to copy
      */
     public SynchronizedSummaryStatistics(SynchronizedSummaryStatistics original) {
@@ -66,7 +66,7 @@
         super.addValue(value);
     }
 
-    /** 
+    /**
      * {@inheritDoc}
      */
     @Override
@@ -146,7 +146,7 @@
         return super.toString();
     }
 
-    /** 
+    /**
      * {@inheritDoc}
      */
     @Override
@@ -297,26 +297,26 @@
     public synchronized void setVarianceImpl(StorelessUnivariateStatistic varianceImpl) {
         super.setVarianceImpl(varianceImpl);
     }
-    
+
     /**
      * Returns a copy of this SynchronizedSummaryStatistics instance with the
      * same internal state.
-     * 
+     *
      * @return a copy of this
      */
     @Override
     public synchronized SynchronizedSummaryStatistics copy() {
-        SynchronizedSummaryStatistics result = 
+        SynchronizedSummaryStatistics result =
             new SynchronizedSummaryStatistics();
         copy(this, result);
-        return result; 
+        return result;
     }
-     
+
     /**
      * Copies source to dest.
      * <p>Neither source nor dest can be null.</p>
      * <p>Acquires synchronization lock on source, then dest before copying.</p>
-     * 
+     *
      * @param source SynchronizedSummaryStatistics to copy
      * @param dest SynchronizedSummaryStatistics to copy to
      * @throws NullPointerException if either source or dest is null
@@ -329,5 +329,5 @@
             }
         }
     }
-    
+
 }

Modified: commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/UnivariateStatistic.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/UnivariateStatistic.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/UnivariateStatistic.java (original)
+++ commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/UnivariateStatistic.java Sat Sep  5 17:36:48 2009
@@ -19,14 +19,14 @@
 
 /**
  * Base interface implemented by all statistics.
- * 
+ *
  * @version $Revision$ $Date$
  */
 public interface UnivariateStatistic {
 
     /**
      * Returns the result of evaluating the statistic over the input array.
-     * 
+     *
      * @param values input array
      * @return the value of the statistic applied to the input array
      */
@@ -35,17 +35,17 @@
     /**
      * Returns the result of evaluating the statistic over the specified entries
      * in the input array.
-     * 
+     *
      * @param values the input array
      * @param begin the index of the first element to include
      * @param length the number of elements to include
      * @return the value of the statistic applied to the included array entries
      */
     double evaluate(double[] values, int begin, int length);
-    
+
     /**
      * Returns a copy of the statistic with the same internal state.
-     * 
+     *
      * @return a copy of the statistic
      */
     UnivariateStatistic copy();

Modified: commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/moment/FirstMoment.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/moment/FirstMoment.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/moment/FirstMoment.java (original)
+++ commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/moment/FirstMoment.java Sat Sep  5 17:36:48 2009
@@ -37,32 +37,32 @@
  * <p>
  *  Returns <code>Double.NaN</code> if the dataset is empty.</p>
  * <p>
- * <strong>Note that this implementation is not synchronized.</strong> If 
+ * <strong>Note that this implementation is not synchronized.</strong> If
  * multiple threads access an instance of this class concurrently, and at least
- * one of the threads invokes the <code>increment()</code> or 
+ * one of the threads invokes the <code>increment()</code> or
  * <code>clear()</code> method, it must be synchronized externally.</p>
  *
  * @version $Revision$ $Date$
  */
-public class FirstMoment extends AbstractStorelessUnivariateStatistic 
+public class FirstMoment extends AbstractStorelessUnivariateStatistic
     implements Serializable {
 
     /** Serializable version identifier */
     private static final long serialVersionUID = 6112755307178490473L;
 
-    
+
     /** Count of values that have been added */
     protected long n;
 
     /** First moment of values that have been added */
     protected double m1;
-    
-    /** 
+
+    /**
      * Deviation of most recently added value from previous first moment.
      * Retained to prevent repeated computation in higher order moments.
      */
     protected double dev;
-    
+
     /**
      * Deviation of most recently added value from previous first moment,
      * normalized by previous sample size.  Retained to prevent repeated
@@ -79,18 +79,18 @@
         dev = Double.NaN;
         nDev = Double.NaN;
     }
-    
+
     /**
      * Copy constructor, creates a new {@code FirstMoment} identical
      * to the {@code original}
-     * 
+     *
      * @param original the {@code FirstMoment} instance to copy
      */
      public FirstMoment(FirstMoment original) {
          super();
          copy(original, this);
      }
-    
+
     /**
      * {@inheritDoc}
      */
@@ -131,7 +131,7 @@
     public long getN() {
         return n;
     }
-    
+
     /**
      * {@inheritDoc}
      */
@@ -139,13 +139,13 @@
     public FirstMoment copy() {
         FirstMoment result = new FirstMoment();
         copy(this, result);
-        return result; 
+        return result;
     }
-     
+
     /**
      * Copies source to dest.
      * <p>Neither source nor dest can be null.</p>
-     * 
+     *
      * @param source FirstMoment to copy
      * @param dest FirstMoment to copy to
      * @throws NullPointerException if either source or dest is null

Modified: commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/moment/FourthMoment.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/moment/FourthMoment.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/moment/FourthMoment.java (original)
+++ commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/moment/FourthMoment.java Sat Sep  5 17:36:48 2009
@@ -20,11 +20,11 @@
 
 /**
  * Computes a statistic related to the Fourth Central Moment.  Specifically,
- * what is computed is the sum of 
+ * what is computed is the sum of
  * <p>
  * (x_i - xbar) ^ 4, </p>
  * <p>
- * where the x_i are the 
+ * where the x_i are the
  * sample observations and xbar is the sample mean. </p>
  * <p>
  * The following recursive updating formula is used: </p>
@@ -43,18 +43,18 @@
  * Returns <code>Double.NaN</code> if no data values have been added and
  * returns <code>0</code> if there is just one value in the data set. </p>
  * <p>
- * <strong>Note that this implementation is not synchronized.</strong> If 
+ * <strong>Note that this implementation is not synchronized.</strong> If
  * multiple threads access an instance of this class concurrently, and at least
- * one of the threads invokes the <code>increment()</code> or 
+ * one of the threads invokes the <code>increment()</code> or
  * <code>clear()</code> method, it must be synchronized externally. </p>
- * 
+ *
  * @version $Revision$ $Date$
  */
 public class FourthMoment extends ThirdMoment implements Serializable{
 
     /** Serializable version identifier */
     private static final long serialVersionUID = 4763990447117157611L;
-        
+
     /** fourth moment of values that have been added */
     protected double m4;
 
@@ -65,18 +65,18 @@
         super();
         m4 = Double.NaN;
     }
-    
+
     /**
      * Copy constructor, creates a new {@code FourthMoment} identical
      * to the {@code original}
-     * 
+     *
      * @param original the {@code FourthMoment} instance to copy
      */
      public FourthMoment(FourthMoment original) {
          super();
          copy(original, this);
      }
-    
+
     /**
      * {@inheritDoc}
      */
@@ -91,9 +91,9 @@
 
         double prevM3 = m3;
         double prevM2 = m2;
-        
+
         super.increment(d);
-        
+
         double n0 = n;
 
         m4 = m4 - 4.0 * nDev * prevM3 + 6.0 * nDevSq * prevM2 +
@@ -116,7 +116,7 @@
         super.clear();
         m4 = Double.NaN;
     }
-    
+
     /**
      * {@inheritDoc}
      */
@@ -126,11 +126,11 @@
         copy(this, result);
         return result;
     }
-    
+
     /**
      * Copies source to dest.
      * <p>Neither source nor dest can be null.</p>
-     * 
+     *
      * @param source FourthMoment to copy
      * @param dest FourthMoment to copy to
      * @throws NullPointerException if either source or dest is null
@@ -138,5 +138,5 @@
     public static void copy(FourthMoment source, FourthMoment dest) {
         ThirdMoment.copy(source, dest);
         dest.m4 = source.m4;
-    }  
+    }
 }

Modified: commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/moment/GeometricMean.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/moment/GeometricMean.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/moment/GeometricMean.java (original)
+++ commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/moment/GeometricMean.java Sat Sep  5 17:36:48 2009
@@ -31,27 +31,27 @@
  * <code> exp( 1/n  (sum of logs) ).</code>  Therefore, </p>
  * <ul>
  * <li>If any of values are < 0, the result is <code>NaN.</code></li>
- * <li>If all values are non-negative and less than 
- * <code>Double.POSITIVE_INFINITY</code>,  but at least one value is 0, the 
+ * <li>If all values are non-negative and less than
+ * <code>Double.POSITIVE_INFINITY</code>,  but at least one value is 0, the
  * result is <code>0.</code></li>
- * <li>If both <code>Double.POSITIVE_INFINITY</code> and 
+ * <li>If both <code>Double.POSITIVE_INFINITY</code> and
  * <code>Double.NEGATIVE_INFINITY</code> are among the values, the result is
  * <code>NaN.</code></li>
  * </ul> </p>
  * <p>
- * <strong>Note that this implementation is not synchronized.</strong> If 
+ * <strong>Note that this implementation is not synchronized.</strong> If
  * multiple threads access an instance of this class concurrently, and at least
- * one of the threads invokes the <code>increment()</code> or 
+ * one of the threads invokes the <code>increment()</code> or
  * <code>clear()</code> method, it must be synchronized externally.</p>
- * 
+ *
  *
  * @version $Revision$ $Date$
  */
 public class GeometricMean extends AbstractStorelessUnivariateStatistic implements Serializable {
 
     /** Serializable version identifier */
-    private static final long serialVersionUID = -8178734905303459453L;  
-    
+    private static final long serialVersionUID = -8178734905303459453L;
+
     /** Wrapped SumOfLogs instance */
     private StorelessUnivariateStatistic sumOfLogs;
 
@@ -61,18 +61,18 @@
     public GeometricMean() {
         sumOfLogs = new SumOfLogs();
     }
-    
+
     /**
      * Copy constructor, creates a new {@code GeometricMean} identical
      * to the {@code original}
-     * 
+     *
      * @param original the {@code GeometricMean} instance to copy
      */
     public GeometricMean(GeometricMean original) {
         super();
         copy(original, this);
     }
-    
+
     /**
      * {@inheritDoc}
      */
@@ -82,7 +82,7 @@
         copy(this, result);
         return result;
     }
-    
+
     /**
      * Create a GeometricMean instance using the given SumOfLogs instance
      * @param sumOfLogs sum of logs instance to use for computation
@@ -90,7 +90,7 @@
     public GeometricMean(SumOfLogs sumOfLogs) {
         this.sumOfLogs = sumOfLogs;
     }
-    
+
     /**
      * {@inheritDoc}
      */
@@ -126,7 +126,7 @@
      * See {@link GeometricMean} for details on the computing algorithm.</p>
      * <p>
      * Throws <code>IllegalArgumentException</code> if the array is null.</p>
-     * 
+     *
      * @param values input array containing the values
      * @param begin first array element to include
      * @param length the number of elements to include
@@ -141,23 +141,23 @@
         return Math.exp(
             sumOfLogs.evaluate(values, begin, length) / length);
     }
-    
+
     /**
      * {@inheritDoc}
      */
     public long getN() {
         return sumOfLogs.getN();
     }
-    
+
     /**
      * <p>Sets the implementation for the sum of logs.</p>
      * <p>This method must be activated before any data has been added - i.e.,
-     * before {@link #increment(double) increment} has been used to add data; 
+     * before {@link #increment(double) increment} has been used to add data;
      * otherwise an IllegalStateException will be thrown.</p>
-     * 
+     *
      * @param sumLogImpl the StorelessUnivariateStatistic instance to use
      * for computing the log sum
-     * @throws IllegalStateException if data has already been added 
+     * @throws IllegalStateException if data has already been added
      *  (i.e if n > 0)
      */
     public void setSumLogImpl(
@@ -165,20 +165,20 @@
         checkEmpty();
         this.sumOfLogs = sumLogImpl;
     }
-    
+
     /**
      * Returns the currently configured sum of logs implementation
-     * 
+     *
      * @return the StorelessUnivariateStatistic implementing the log sum
      */
     public StorelessUnivariateStatistic getSumLogImpl() {
         return sumOfLogs;
     }
-    
+
     /**
      * Copies source to dest.
      * <p>Neither source nor dest can be null.</p>
-     * 
+     *
      * @param source GeometricMean to copy
      * @param dest GeometricMean to copy to
      * @throws NullPointerException if either source or dest is null
@@ -186,8 +186,8 @@
     public static void copy(GeometricMean source, GeometricMean dest) {
         dest.sumOfLogs = source.sumOfLogs.copy();
     }
-    
-    
+
+
     /**
      * Throws IllegalStateException if n > 0.
      */
@@ -199,4 +199,4 @@
         }
     }
 
-}
\ No newline at end of file
+}

Modified: commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/moment/Kurtosis.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/moment/Kurtosis.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/moment/Kurtosis.java (original)
+++ commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/moment/Kurtosis.java Sat Sep  5 17:36:48 2009
@@ -35,22 +35,22 @@
  *  Note that this statistic is undefined for n < 4.  <code>Double.Nan</code>
  *  is returned when there is not sufficient data to compute the statistic.</p>
  * <p>
- * <strong>Note that this implementation is not synchronized.</strong> If 
+ * <strong>Note that this implementation is not synchronized.</strong> If
  * multiple threads access an instance of this class concurrently, and at least
- * one of the threads invokes the <code>increment()</code> or 
+ * one of the threads invokes the <code>increment()</code> or
  * <code>clear()</code> method, it must be synchronized externally.</p>
- * 
+ *
  * @version $Revision$ $Date$
  */
 public class Kurtosis extends AbstractStorelessUnivariateStatistic  implements Serializable {
 
     /** Serializable version identifier */
-    private static final long serialVersionUID = 2784465764798260919L;  
-      
+    private static final long serialVersionUID = 2784465764798260919L;
+
     /**Fourth Moment on which this statistic is based */
     protected FourthMoment moment;
 
-    /** 
+    /**
      * Determines whether or not this statistic can be incremented or cleared.
      * <p>
      * Statistics based on (constructed from) external moments cannot
@@ -68,18 +68,18 @@
 
     /**
      * Construct a Kurtosis from an external moment
-     * 
+     *
      * @param m4 external Moment
      */
     public Kurtosis(final FourthMoment m4) {
         incMoment = false;
         this.moment = m4;
     }
-    
+
     /**
      * Copy constructor, creates a new {@code Kurtosis} identical
      * to the {@code original}
-     * 
+     *
      * @param original the {@code Kurtosis} instance to copy
      */
     public Kurtosis(Kurtosis original) {
@@ -139,17 +139,17 @@
     public long getN() {
         return moment.getN();
     }
-    
+
     /* UnvariateStatistic Approach  */
 
     /**
      * Returns the kurtosis of the entries in the specified portion of the
-     * input array.  
+     * input array.
      * <p>
      * See {@link Kurtosis} for details on the computing algorithm.</p>
      * <p>
      * Throws <code>IllegalArgumentException</code> if the array is null.</p>
-     * 
+     *
      * @param values the input array
      * @param begin index of the first array element to include
      * @param length the number of elements to include
@@ -160,17 +160,17 @@
      */
     @Override
     public double evaluate(final double[] values,final int begin, final int length) {
-        // Initialize the kurtosis  
-        double kurt = Double.NaN;   
-        
-        if (test(values, begin, length) && length > 3) {       
-            
+        // Initialize the kurtosis
+        double kurt = Double.NaN;
+
+        if (test(values, begin, length) && length > 3) {
+
             // Compute the mean and standard deviation
             Variance variance = new Variance();
             variance.incrementAll(values, begin, length);
             double mean = variance.moment.m1;
             double stdDev = Math.sqrt(variance.getResult());
-            
+
             // Sum the ^4 of the distance from the mean divided by the
             // standard deviation
             double accum3 = 0.0;
@@ -178,21 +178,21 @@
                 accum3 += Math.pow((values[i] - mean), 4.0);
             }
             accum3 /= Math.pow(stdDev, 4.0d);
-            
+
             // Get N
             double n0 = length;
-            
+
             double coefficientOne =
                 (n0 * (n0 + 1)) / ((n0 - 1) * (n0 - 2) * (n0 - 3));
             double termTwo =
                 ((3 * Math.pow(n0 - 1, 2.0)) / ((n0 - 2) * (n0 - 3)));
-            
+
             // Calculate kurtosis
             kurt = (coefficientOne * accum3) - termTwo;
-        }       
+        }
         return kurt;
     }
-    
+
     /**
      * {@inheritDoc}
      */
@@ -202,11 +202,11 @@
         copy(this, result);
         return result;
     }
-    
+
     /**
      * Copies source to dest.
      * <p>Neither source nor dest can be null.</p>
-     * 
+     *
      * @param source Kurtosis to copy
      * @param dest Kurtosis to copy to
      * @throws NullPointerException if either source or dest is null

Modified: commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/moment/Mean.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/moment/Mean.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/moment/Mean.java (original)
+++ commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/moment/Mean.java Sat Sep  5 17:36:48 2009
@@ -48,23 +48,23 @@
  * <p>
  *  Returns <code>Double.NaN</code> if the dataset is empty.
  * </p>
- * <strong>Note that this implementation is not synchronized.</strong> If 
+ * <strong>Note that this implementation is not synchronized.</strong> If
  * multiple threads access an instance of this class concurrently, and at least
- * one of the threads invokes the <code>increment()</code> or 
+ * one of the threads invokes the <code>increment()</code> or
  * <code>clear()</code> method, it must be synchronized externally.
- * 
+ *
  * @version $Revision$ $Date$
  */
-public class Mean extends AbstractStorelessUnivariateStatistic 
+public class Mean extends AbstractStorelessUnivariateStatistic
     implements Serializable {
 
     /** Serializable version identifier */
-    private static final long serialVersionUID = -1296043746617791564L;    
-    
+    private static final long serialVersionUID = -1296043746617791564L;
+
     /** First moment on which this statistic is based. */
     protected FirstMoment moment;
 
-    /** 
+    /**
      * Determines whether or not this statistic can be incremented or cleared.
      * <p>
      * Statistics based on (constructed from) external moments cannot

Modified: commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/moment/SecondMoment.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/moment/SecondMoment.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/moment/SecondMoment.java (original)
+++ commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/moment/SecondMoment.java Sat Sep  5 17:36:48 2009
@@ -35,18 +35,18 @@
  * Returns <code>Double.NaN</code> if no data values have been added and
  * returns <code>0</code> if there is just one value in the data set.</p>
  * <p>
- * <strong>Note that this implementation is not synchronized.</strong> If 
+ * <strong>Note that this implementation is not synchronized.</strong> If
  * multiple threads access an instance of this class concurrently, and at least
- * one of the threads invokes the <code>increment()</code> or 
+ * one of the threads invokes the <code>increment()</code> or
  * <code>clear()</code> method, it must be synchronized externally.</p>
- * 
+ *
  * @version $Revision$ $Date$
  */
 public class SecondMoment extends FirstMoment implements Serializable {
 
     /** Serializable version identifier */
-    private static final long serialVersionUID = 3942403127395076445L;  
-      
+    private static final long serialVersionUID = 3942403127395076445L;
+
     /** second moment of values that have been added */
     protected double m2;
 
@@ -57,18 +57,18 @@
         super();
         m2 = Double.NaN;
     }
-    
+
     /**
      * Copy constructor, creates a new {@code SecondMoment} identical
      * to the {@code original}
-     * 
+     *
      * @param original the {@code SecondMoment} instance to copy
      */
     public SecondMoment(SecondMoment original) {
         super(original);
         this.m2 = original.m2;
     }
-    
+
     /**
      * {@inheritDoc}
      */
@@ -97,7 +97,7 @@
     public double getResult() {
         return m2;
     }
-    
+
     /**
      * {@inheritDoc}
      */
@@ -105,13 +105,13 @@
     public SecondMoment copy() {
         SecondMoment result = new SecondMoment();
         copy(this, result);
-        return result; 
+        return result;
     }
-    
+
     /**
      * Copies source to dest.
      * <p>Neither source nor dest can be null.</p>
-     * 
+     *
      * @param source SecondMoment to copy
      * @param dest SecondMoment to copy to
      * @throws NullPointerException if either source or dest is null

Modified: commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/moment/Skewness.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/moment/Skewness.java?rev=811685&r1=811684&r2=811685&view=diff
==============================================================================
--- commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/moment/Skewness.java (original)
+++ commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/descriptive/moment/Skewness.java Sat Sep  5 17:36:48 2009
@@ -27,25 +27,25 @@
  * <p>
  * skewness = [n / (n -1) (n - 2)] sum[(x_i - mean)^3] / std^3 </p>
  * <p>
- * where n is the number of values, mean is the {@link Mean} and std is the 
+ * where n is the number of values, mean is the {@link Mean} and std is the
  * {@link StandardDeviation} </p>
  * <p>
- * <strong>Note that this implementation is not synchronized.</strong> If 
+ * <strong>Note that this implementation is not synchronized.</strong> If
  * multiple threads access an instance of this class concurrently, and at least
- * one of the threads invokes the <code>increment()</code> or 
+ * one of the threads invokes the <code>increment()</code> or
  * <code>clear()</code> method, it must be synchronized externally. </p>
- * 
+ *
  * @version $Revision$ $Date$
  */
 public class Skewness extends AbstractStorelessUnivariateStatistic implements Serializable {
 
     /** Serializable version identifier */
-    private static final long serialVersionUID = 7101857578996691352L;    
-    
+    private static final long serialVersionUID = 7101857578996691352L;
+
     /** Third moment on which this statistic is based */
     protected ThirdMoment moment = null;
 
-     /** 
+     /**
      * Determines whether or not this statistic can be incremented or cleared.
      * <p>
      * Statistics based on (constructed from) external moments cannot
@@ -69,11 +69,11 @@
         incMoment = false;
         this.moment = m3;
     }
-     
+
     /**
      * Copy constructor, creates a new {@code Skewness} identical
      * to the {@code original}
-     * 
+     *
      * @param original the {@code Skewness} instance to copy
      */
     public Skewness(Skewness original) {
@@ -94,12 +94,12 @@
      * Returns the value of the statistic based on the values that have been added.
      * <p>
      * See {@link Skewness} for the definition used in the computation.</p>
-     * 
+     *
      * @return the skewness of the available values.
      */
     @Override
     public double getResult() {
-        
+
         if (moment.n < 3) {
             return Double.NaN;
         }
@@ -119,7 +119,7 @@
     public long getN() {
         return moment.getN();
     }
-    
+
     /**
      * {@inheritDoc}
      */
@@ -137,7 +137,7 @@
      * See {@link Skewness} for the definition used in the computation.</p>
      * <p>
      * Throws <code>IllegalArgumentException</code> if the array is null.</p>
-     * 
+     *
      * @param values the input array
      * @param begin the index of the first array element to include
      * @param length the number of elements to include
@@ -147,7 +147,7 @@
      *  parameters are not valid
      */
     @Override
-    public double evaluate(final double[] values,final int begin, 
+    public double evaluate(final double[] values,final int begin,
             final int length) {
 
         // Initialize the skewness
@@ -157,7 +157,7 @@
             Mean mean = new Mean();
             // Get the mean and the standard deviation
             double m = mean.evaluate(values, begin, length);
-            
+
             // Calc the std, this is implemented here instead
             // of using the standardDeviation method eliminate
             // a duplicate pass to get the mean
@@ -169,22 +169,22 @@
             }
             double stdDev = Math.sqrt((accum - (Math.pow(accum2, 2) / length)) /
                     (length - 1));
-            
+
             double accum3 = 0.0;
             for (int i = begin; i < begin + length; i++) {
                 accum3 += Math.pow(values[i] - m, 3.0d);
             }
             accum3 /= Math.pow(stdDev, 3.0d);
-            
+
             // Get N
             double n0 = length;
-            
+
             // Calculate skewness
             skew = (n0 / ((n0 - 1) * (n0 - 2))) * accum3;
         }
         return skew;
     }
-    
+
     /**
      * {@inheritDoc}
      */
@@ -194,11 +194,11 @@
         copy(this, result);
         return result;
     }
-    
+
     /**
      * Copies source to dest.
      * <p>Neither source nor dest can be null.</p>
-     * 
+     *
      * @param source Skewness to copy
      * @param dest Skewness to copy to
      * @throws NullPointerException if either source or dest is null



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