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https://issues.apache.org/jira/browse/MATH-1140?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Anders Conbere closed MATH-1140.
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Resolution: Fixed
Ouch, somewhat embarrassed to say that our experimental data was just often
large enough that we often hit 0 :-/
> Incorrect result from MannWhitneyUTest#mannWhitneyUTest with large datasets
> ---------------------------------------------------------------------------
>
> Key: MATH-1140
> URL: https://issues.apache.org/jira/browse/MATH-1140
> Project: Commons Math
> Issue Type: Bug
> Affects Versions: 3.3
> Reporter: Anders Conbere
> Priority: Minor
>
> On large datasets MannWhitneyUTest#mannWhitneyUTest returns the double value
> 0.0 instead of the correct p-value. I suspect this is an overflow but haven't
> been able to trace it down yet.
> I'm afraid I'm not very good at java, but I'm including a link to a public
> repository where you can reproduce the issue, unfortunately my implementation
> is written in clojure.
> https://github.com/aconbere/apache-commons-mann-whitney-bug
> The summary is that by calling MannWhitneyUTest#mannWhitneyUTest with two
> randomly generated arrays (50k elements with a max value of 300) I can
> reliably reproduce the result 0.0. By reducing that to something more modest
> like 2k I get correct p-value calculations.
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