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https://issues.apache.org/jira/browse/MATH-437?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12933077#action_12933077
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Richard Simard commented on MATH-437:
-------------------------------------
http://www.mail-archive.com/[email protected]/msg15829.html
F(n, x) = F(200, 0.031111):
Lecuyer (2.0 ms.) = 0.012916146481628863
KolmogorovSmirnovDistribution exact (51902.0 ms.) = 0.012149763742041911
KolmogorovSmirnovDistribution !exact (9.0 ms.) = 0.012149763742041922
The argument x that you used in the Simard-L'écuyer program is not the same
that you used for the other two programs. Of course you then get
very different results. If I compute exactly in Mathematica, I obtain
F(200, 0.031111) = 0.0129161464816289
which is very different than your exact results above and agrees well with our
program.
=================================================
Richard Simard <[email protected]>
Laboratoire de simulation et d'optimisation
Université de Montréal, IRO
> Kolmogorov Smirnov Distribution
> -------------------------------
>
> Key: MATH-437
> URL: https://issues.apache.org/jira/browse/MATH-437
> Project: Commons Math
> Issue Type: New Feature
> Reporter: Mikkel Meyer Andersen
> Assignee: Mikkel Meyer Andersen
> Priority: Minor
> Attachments: KolmogorovSmirnovDistribution.java
>
> Original Estimate: 0.25h
> Remaining Estimate: 0.25h
>
> Kolmogorov-Smirnov test (see [1]) is used to test if one sample against a
> known probability density functions or if two samples are from the same
> distribution. To evaluate the test statistic, the Kolmogorov-Smirnov
> distribution is used. Quite good asymptotics exist for the one-sided test,
> but it's more difficult for the two-sided test.
> [1]: http://en.wikipedia.org/wiki/Kolmogorov%E2%80%93Smirnov_test
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