From d7e7b226d87bae7d71072802dfca8b80b55fea19 Mon Sep 17 00:00:00 2001 From: Phil Steitz Date: Fri, 1 Jan 2016 08:50:09 -0700 Subject: [PATCH] Updated User Guide to reflect MATH-1310 fix. --- src/site/xdoc/userguide/stat.xml | 9 ++++----- 1 file changed, 4 insertions(+), 5 deletions(-) diff --git a/src/site/xdoc/userguide/stat.xml b/src/site/xdoc/userguide/stat.xml index 603572752..6a6dd8728 100644 --- a/src/site/xdoc/userguide/stat.xml +++ b/src/site/xdoc/userguide/stat.xml @@ -915,10 +915,9 @@ new KendallsCorrelation().correlation(x, y) Computing the Two-Sided Kolmogorov-Smirnov Distribution by Richard Simard and Pierre L'Ecuyer. In the 2-sample case, estimation by default depends on the number of data points. For small samples, the distribution - is computed exactly; for moderately large samples a Monte Carlo procedure is used, and - for large samples a numerical approximation of the Kolmogorov distribution is used. - Methods to perform each type of p-value estimation are also exposed directly. See - the class javadoc for details. + is computed exactly and for large samples a numerical approximation of the Kolmogorov + distribution is used. Methods to perform each type of p-value estimation are also exposed + directly. See the class javadoc for details.

@@ -1237,7 +1236,7 @@ final double d = TestUtils.kolmogorovSmirnovStatistic(x, y); TestUtils.exactP(d, x.length, y.length, false) assuming that the non-strict form of the null hypothesis is desired. Note, however, - that exact computation for anything but very small samples takes a very long time. + that exact computation for large samples takes a long time.