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Added Spearman's correlation. 

git-svn-id: https://svn.apache.org/repos/asf/commons/proper/math/trunk@786940 13f79535-47bb-0310-9956-ffa450edef68
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Phil Steitz 2009-06-21 02:22:09 +00:00
parent b3c7fd661c
commit 4ee03f09ff
1 changed files with 26 additions and 3 deletions
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29
src/site/xdoc/userguide/stat.xml
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@ -543,9 +543,11 @@ new NaturalRanking(NaNStrategy.REMOVED,TiesStrategy.SEQUENTIAL).rank(exampleData
org.apache.commons.math.stat.correlation</a> package computes covariances
and correlations for pairs of arrays or columns of a matrix.
<a href="../apidocs/org/apache/commons/math/stat/correlation/Covariance.html">
Covariance</a> computes covariances and
Covariance</a> computes covariances,
<a href="../apidocs/org/apache/commons/math/stat/correlation/PearsonsCorrelation.html">
PearsonsCorrelation</a> provides Pearson's Product-Moment correlation coefficients.
PearsonsCorrelation</a> provides Pearson's Product-Moment correlation coefficients and
<a href="../apidocs/org/apache/commons/math/stat/correlation/SpearmansCorrelation.html">
SpearmansCorrelation</a> computes Spearman's rank correlation.
</p>
<p>
<strong>Implementation Notes</strong>
@ -560,12 +562,19 @@ new NaturalRanking(NaNStrategy.REMOVED,TiesStrategy.SEQUENTIAL).rank(exampleData
defaults to <code>true.</code>
</li>
<li>
<a href="../apidocs/org/apache/commons/math/stat/correlation/PearsonsCorrelation.html">
<a href="../apidocs/org/apache/commons/math/stat/correlation/PearsonsCorrelation.html">
PearsonsCorrelation</a> computes correlations defined by the formula <br></br>
<code>cor(X, Y) = sum[(x<sub>i</sub> - E(X))(y<sub>i</sub> - E(Y))] / [(n - 1)s(X)s(Y)]</code><br/>
where <code>E(X)</code> and <code>E(Y)</code> are means of <code>X</code> and <code>Y</code>
and <code>s(X)</code>, <code>s(Y)</code> are standard deviations.
</li>
<li>
<a href="../apidocs/org/apache/commons/math/stat/correlation/SpearmansCorrelation.html">
SpearmansCorrelation</a> applies a rank transformation to the input data and computes Pearson's
correlation on the ranked data. The ranking algorithm is configurable. By default,
<a href="../apidocs/org/apache/commons/math/stat/ranking/NaturalRanking.html">
NaturalRanking</a> with default strategies for handling ties and NaN values is used.
</li>
</ul>
</p>
<p>
@ -657,6 +666,20 @@ new PearsonsCorrelation(data).getCorrelationPValues().getEntry(0,1)
between the two columns of data is significant at the 99% level.
</dd>
<br></br>
<dt><strong>Spearman's rank correlation coefficient</strong></dt>
<br></br>
<dd>To compute the Spearman's rank-moment correlation between two double arrays
<code>x</code> and <code>y</code>:
<source>
new SpearmansCorrelation().correlation(x, y)
</source>
This is equivalent to
<source>
RankingAlgorithm ranking = new NaturalRanking();
new PearsonsCorrelation().correlation(ranking.rank(x), ranking.rank(y))
</source>
</dd>
<br></br>
</dl>
</p>
</subsection>