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Posted to commits@commons.apache.org by ra...@apache.org on 2017/05/12 22:06:03 UTC
[4/5] [math] Fix javadoc issues
Fix javadoc issues
Project: http://git-wip-us.apache.org/repos/asf/commons-math/repo
Commit: http://git-wip-us.apache.org/repos/asf/commons-math/commit/69f13aed
Tree: http://git-wip-us.apache.org/repos/asf/commons-math/tree/69f13aed
Diff: http://git-wip-us.apache.org/repos/asf/commons-math/diff/69f13aed
Branch: refs/heads/master
Commit: 69f13aed99c256eb5f9a4b1f293836f37b52402f
Parents: b6bcbff
Author: Ray DeCampo <ra...@decampo.org>
Authored: Fri May 12 18:00:58 2017 -0400
Committer: Ray DeCampo <ra...@decampo.org>
Committed: Fri May 12 18:00:58 2017 -0400
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.../stat/regression/AbstractMultipleLinearRegression.java | 4 ++--
.../math4/stat/regression/MillerUpdatingRegression.java | 2 +-
.../stat/regression/OLSMultipleLinearRegression.java | 10 +++++-----
.../commons/math4/stat/regression/RegressionResults.java | 6 +++---
.../commons/math4/stat/regression/SimpleRegression.java | 6 +++---
5 files changed, 14 insertions(+), 14 deletions(-)
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http://git-wip-us.apache.org/repos/asf/commons-math/blob/69f13aed/src/main/java/org/apache/commons/math4/stat/regression/AbstractMultipleLinearRegression.java
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diff --git a/src/main/java/org/apache/commons/math4/stat/regression/AbstractMultipleLinearRegression.java b/src/main/java/org/apache/commons/math4/stat/regression/AbstractMultipleLinearRegression.java
index d7036e3..78b9460 100644
--- a/src/main/java/org/apache/commons/math4/stat/regression/AbstractMultipleLinearRegression.java
+++ b/src/main/java/org/apache/commons/math4/stat/regression/AbstractMultipleLinearRegression.java
@@ -90,7 +90,7 @@ public abstract class AbstractMultipleLinearRegression implements
* 4 5 6
* 7 8 9
* </pre>
- * </p>
+ *
* <p>Note that there is no need to add an initial unitary column (column of 1's) when
* specifying a model including an intercept term. If {@link #isNoIntercept()} is <code>true</code>,
* the X matrix will be created without an initial column of "1"s; otherwise this column will
@@ -99,7 +99,7 @@ public abstract class AbstractMultipleLinearRegression implements
* <p>Throws IllegalArgumentException if any of the following preconditions fail:
* <ul><li><code>data</code> cannot be null</li>
* <li><code>data.length = nobs * (nvars + 1)</code></li>
- * <li><code>nobs > nvars</code></li></ul>
+ * <li>{@code nobs > nvars}</li></ul>
*
* @param data input data array
* @param nobs number of observations (rows)
http://git-wip-us.apache.org/repos/asf/commons-math/blob/69f13aed/src/main/java/org/apache/commons/math4/stat/regression/MillerUpdatingRegression.java
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diff --git a/src/main/java/org/apache/commons/math4/stat/regression/MillerUpdatingRegression.java b/src/main/java/org/apache/commons/math4/stat/regression/MillerUpdatingRegression.java
index abc8fea..0558719 100644
--- a/src/main/java/org/apache/commons/math4/stat/regression/MillerUpdatingRegression.java
+++ b/src/main/java/org/apache/commons/math4/stat/regression/MillerUpdatingRegression.java
@@ -595,7 +595,7 @@ public class MillerUpdatingRegression implements UpdatingMultipleLinearRegressio
* model, then the usual simple correlations are returned.</p>
*
* <p>If IN = 0, the value returned in array CORMAT for the correlation
- * of variables Xi & Xj is: <pre>
+ * of variables Xi & Xj is: <pre>
* sum ( Xi.Xj ) / Sqrt ( sum (Xi^2) . sum (Xj^2) )</pre>
*
* <p>On return, array CORMAT contains the upper triangle of the matrix of
http://git-wip-us.apache.org/repos/asf/commons-math/blob/69f13aed/src/main/java/org/apache/commons/math4/stat/regression/OLSMultipleLinearRegression.java
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diff --git a/src/main/java/org/apache/commons/math4/stat/regression/OLSMultipleLinearRegression.java b/src/main/java/org/apache/commons/math4/stat/regression/OLSMultipleLinearRegression.java
index 113a04f..637e4fe 100644
--- a/src/main/java/org/apache/commons/math4/stat/regression/OLSMultipleLinearRegression.java
+++ b/src/main/java/org/apache/commons/math4/stat/regression/OLSMultipleLinearRegression.java
@@ -183,9 +183,9 @@ public class OLSMultipleLinearRegression extends AbstractMultipleLinearRegressio
}
/**
- * Returns the R-Squared statistic, defined by the formula <pre>
+ * Returns the R-Squared statistic, defined by the formula <div style="white-space: pre"><code>
* R<sup>2</sup> = 1 - SSR / SSTO
- * </pre>
+ * </code></div>
* where SSR is the {@link #calculateResidualSumOfSquares() sum of squared residuals}
* and SSTO is the {@link #calculateTotalSumOfSquares() total sum of squares}
*
@@ -201,12 +201,12 @@ public class OLSMultipleLinearRegression extends AbstractMultipleLinearRegressio
}
/**
- * <p>Returns the adjusted R-squared statistic, defined by the formula <pre>
+ * <p>Returns the adjusted R-squared statistic, defined by the formula <div style="white-space: pre"><code>
* R<sup>2</sup><sub>adj</sub> = 1 - [SSR (n - 1)] / [SSTO (n - p)]
- * </pre>
+ * </code></div>
* where SSR is the {@link #calculateResidualSumOfSquares() sum of squared residuals},
* SSTO is the {@link #calculateTotalSumOfSquares() total sum of squares}, n is the number
- * of observations and p is the number of parameters estimated (including the intercept).</p>
+ * of observations and p is the number of parameters estimated (including the intercept).
*
* <p>If the regression is estimated without an intercept term, what is returned is <pre>
* <code> 1 - (1 - {@link #calculateRSquared()}) * (n / (n - p)) </code>
http://git-wip-us.apache.org/repos/asf/commons-math/blob/69f13aed/src/main/java/org/apache/commons/math4/stat/regression/RegressionResults.java
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diff --git a/src/main/java/org/apache/commons/math4/stat/regression/RegressionResults.java b/src/main/java/org/apache/commons/math4/stat/regression/RegressionResults.java
index 8d15d49..8a2a7fa 100644
--- a/src/main/java/org/apache/commons/math4/stat/regression/RegressionResults.java
+++ b/src/main/java/org/apache/commons/math4/stat/regression/RegressionResults.java
@@ -363,12 +363,12 @@ public class RegressionResults implements Serializable {
}
/**
- * <p>Returns the adjusted R-squared statistic, defined by the formula <pre>
+ * <p>Returns the adjusted R-squared statistic, defined by the formula <div style="white-space: pre"><code>
* R<sup>2</sup><sub>adj</sub> = 1 - [SSR (n - 1)] / [SSTO (n - p)]
- * </pre>
+ * </code></div>
* where SSR is the sum of squared residuals},
* SSTO is the total sum of squares}, n is the number
- * of observations and p is the number of parameters estimated (including the intercept).</p>
+ * of observations and p is the number of parameters estimated (including the intercept).
*
* <p>If the regression is estimated without an intercept term, what is returned is <pre>
* <code> 1 - (1 - {@link #getRSquared()} ) * (n / (n - p)) </code>
http://git-wip-us.apache.org/repos/asf/commons-math/blob/69f13aed/src/main/java/org/apache/commons/math4/stat/regression/SimpleRegression.java
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diff --git a/src/main/java/org/apache/commons/math4/stat/regression/SimpleRegression.java b/src/main/java/org/apache/commons/math4/stat/regression/SimpleRegression.java
index 201c172..1940c02 100644
--- a/src/main/java/org/apache/commons/math4/stat/regression/SimpleRegression.java
+++ b/src/main/java/org/apache/commons/math4/stat/regression/SimpleRegression.java
@@ -482,7 +482,7 @@ public class SimpleRegression implements Serializable, UpdatingMultipleLinearReg
* This is defined as SSTO
* <a href="http://www.xycoon.com/SumOfSquares.htm">here</a>.</p>
* <p>
- * If <code>n < 2</code>, this returns <code>Double.NaN</code>.</p>
+ * If {@code n < 2}, this returns <code>Double.NaN</code>.</p>
*
* @return sum of squared deviations of y values
*/
@@ -679,7 +679,7 @@ public class SimpleRegression implements Serializable, UpdatingMultipleLinearReg
* model, or if there is no variation in x, this returns
* <code>Double.NaN</code>.
* </li>
- * <li><code>(0 < alpha < 1)</code>; otherwise an
+ * <li>{@code (0 < alpha < 1)}; otherwise an
* <code>OutOfRangeException</code> is thrown.
* </li></ul>
*
@@ -708,7 +708,7 @@ public class SimpleRegression implements Serializable, UpdatingMultipleLinearReg
* Specifically, the returned value is the smallest <code>alpha</code>
* such that the slope confidence interval with significance level
* equal to <code>alpha</code> does not include <code>0</code>.
- * On regression output, this is often denoted <code>Prob(|t| > 0)</code>
+ * On regression output, this is often denoted {@code Prob(|t| > 0)}
* </p><p>
* <strong>Usage Note</strong>:<br>
* The validity of this statistic depends on the assumption that the