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From Mikkel Meyer Andersen <>
Subject Re: [jira] Commented: (MATH-431) New tests: Wilcoxon signed-rank test and Mann-Whitney U
Date Sat, 06 Nov 2010 16:44:58 GMT
2010/11/6 Phil Steitz (JIRA) <>:
>    [
> Phil Steitz commented on MATH-431:
> ----------------------------------
> +1 for including both of these tests.  Then on to MATH-228
Anything I should do in regard to that?
> Interesting approach for the exact algorithm for Wilcoxon.  If we stay with this, we
should ack the original author of the algorithm in the javadoc.  Looks OK to use.
Agree - both on the approach and legal part! Does the author need to
sign anything but write a mail?
>  Regarding the difference from R, what I usually do in this case is look at the R sources
to try to explain the difference.  Most likely in this case, what is going on is they are
using a different estimation algorithm for small n or treating ties differently.  The ranking
options that we use were largely adapted from R, so if that is the problem, it should be easy
to test.  We need to convince ourselves that ours is better or at least a legitimate alternative.
 I will take a close look this evening, but it looks like the algorithm you are using should
be exact.  If we can't reconcile the difference with R, it would be good to find a way to
validate correct functioning of the algorithm by manufacturing reference data with known p.
I'll try to investigate the difference, hopefully tomorrow, so that
formal tests can be written and included.
>> New tests: Wilcoxon signed-rank test and Mann-Whitney U
>> -------------------------------------------------------
>>                 Key: MATH-431
>>                 URL:
>>             Project: Commons Math
>>          Issue Type: New Feature
>>            Reporter: Mikkel Meyer Andersen
>>            Assignee: Mikkel Meyer Andersen
>>            Priority: Minor
>>         Attachments:,,,
>>   Original Estimate: 4h
>>  Remaining Estimate: 4h
>> Wilcoxon signed-rank test and Mann-Whitney U are commonly used non-parametric statistical
hypothesis tests (e.g. instead of various t-tests when normality is not present).
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