svn commit: r1160068 - /commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/correlation/Covariance.java

[psteitz]

Author: psteitz
Date: Sun Aug 21 21:18:34 2011
New Revision: 1160068

URL: http://svn.apache.org/viewvc?rev=1160068&view=rev
Log:
Replaced deprecated exception; fixed javadoc typo.

Modified:
    
commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/correlation/Covariance.java

Modified: 
commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/correlation/Covariance.java
URL: 
http://svn.apache.org/viewvc/commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/correlation/Covariance.java?rev=1160068&r1=1160067&r2=1160068&view=diff
==============================================================================
--- 
commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/correlation/Covariance.java
 (original)
+++ 
commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/correlation/Covariance.java
 Sun Aug 21 21:18:34 2011
@@ -16,7 +16,7 @@
  */
 package org.apache.commons.math.stat.correlation;
 
-import org.apache.commons.math.MathRuntimeException;
+import org.apache.commons.math.exception.MathIllegalArgumentException;
 import org.apache.commons.math.exception.util.LocalizedFormats;
 import org.apache.commons.math.linear.RealMatrix;
 import org.apache.commons.math.linear.BlockRealMatrix;
@@ -195,7 +195,7 @@ public class Covariance {
     }
 
     /**
-     * Create a covariance matrix from a rectangual array whose columns 
represent
+     * Create a covariance matrix from a rectangular array whose columns 
represent
      * covariates. Covariances are computed using the bias-corrected formula.
      * @param data input array (must have at least two columns and two rows)
      * @return covariance matrix
@@ -223,11 +223,11 @@ public class Covariance {
         double result = 0d;
         int length = xArray.length;
         if (length != yArray.length) {
-            throw MathRuntimeException.createIllegalArgumentException(
+            throw new MathIllegalArgumentException(
                   LocalizedFormats.DIMENSIONS_MISMATCH_SIMPLE, length, 
yArray.length);
         } else if (length < 2) {
-            throw MathRuntimeException.createIllegalArgumentException(
-                  LocalizedFormats.INSUFFICIENT_DIMENSION, length, 2);
+            throw new MathIllegalArgumentException(
+                  LocalizedFormats.INSUFFICIENT_OBSERVED_POINTS_IN_SAMPLE, 
length, 2);
         } else {
             double xMean = mean.evaluate(xArray);
             double yMean = mean.evaluate(yArray);
@@ -266,7 +266,7 @@ public class Covariance {
         int nRows = matrix.getRowDimension();
         int nCols = matrix.getColumnDimension();
         if (nRows < 2 || nCols < 2) {
-            throw MathRuntimeException.createIllegalArgumentException(
+            throw new MathIllegalArgumentException(
                     LocalizedFormats.INSUFFICIENT_ROWS_AND_COLUMNS,
                     nRows, nCols);
         }