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From l..@apache.org
Subject svn commit: r1073458 - /commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/regression/AbstractMultipleLinearRegression.java
Date Tue, 22 Feb 2011 19:17:51 GMT
Author: luc
Date: Tue Feb 22 19:17:51 2011
New Revision: 1073458

URL: http://svn.apache.org/viewvc?rev=1073458&view=rev
Log:
added missing @since tags
JIRA: MATH-529

Modified:
    commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/regression/AbstractMultipleLinearRegression.java

Modified: commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/regression/AbstractMultipleLinearRegression.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/regression/AbstractMultipleLinearRegression.java?rev=1073458&r1=1073457&r2=1073458&view=diff
==============================================================================
--- commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/regression/AbstractMultipleLinearRegression.java
(original)
+++ commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/regression/AbstractMultipleLinearRegression.java
Tue Feb 22 19:17:51 2011
@@ -44,6 +44,7 @@ public abstract class AbstractMultipleLi
 
     /**
      * @return true if the model has no intercept term; false otherwise
+     * @since 2.2
      */
     public boolean isNoIntercept() {
         return noIntercept;
@@ -51,6 +52,7 @@ public abstract class AbstractMultipleLi
 
     /**
      * @param noIntercept true means the model is to be estimated without an intercept term
+     * @since 2.2
      */
     public void setNoIntercept(boolean noIntercept) {
         this.noIntercept = noIntercept;
@@ -287,6 +289,7 @@ public abstract class AbstractMultipleLi
      * Estimates the variance of the error.
      *
      * @return estimate of the error variance
+     * @since 2.2
      */
     public double estimateErrorVariance() {
         return calculateErrorVariance();
@@ -297,6 +300,7 @@ public abstract class AbstractMultipleLi
      * Estimates the standard error of the regression.
      *
      * @return regression standard error
+     * @since 2.2
      */
     public double estimateRegressionStandardError() {
         return Math.sqrt(estimateErrorVariance());
@@ -336,6 +340,7 @@ public abstract class AbstractMultipleLi
      * matrix X.
      *
      * @return error variance estimate
+     * @since 2.2
      */
     protected double calculateErrorVariance() {
         RealVector residuals = calculateResiduals();



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