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 <r...@decampo.org> Authored: Fri May 12 18:00:58 2017 -0400 Committer: Ray DeCampo <r...@decampo.org> Committed: Fri May 12 18:00:58 2017 -0400 ---------------------------------------------------------------------- .../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(-) ---------------------------------------------------------------------- http://git-wip-us.apache.org/repos/asf/commons-math/blob/69f13aed/src/main/java/org/apache/commons/math4/stat/regression/AbstractMultipleLinearRegression.java ---------------------------------------------------------------------- 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 ---------------------------------------------------------------------- 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 ---------------------------------------------------------------------- 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 ---------------------------------------------------------------------- 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 ---------------------------------------------------------------------- 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