2010/11/6 Phil Steitz (JIRA) <[email protected]>:
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> https://issues.apache.org/jira/browse/MATH-431?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12929054#action_12929054
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> Phil Steitz commented on MATH-431:
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>
> +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: https://issues.apache.org/jira/browse/MATH-431
>> Project: Commons Math
>> Issue Type: New Feature
>> Reporter: Mikkel Meyer Andersen
>> Assignee: Mikkel Meyer Andersen
>> Priority: Minor
>> Attachments: MannWhitneyUTest.java, MannWhitneyUTestImpl.java,
>> WilcoxonSignedRankTest.java, WilcoxonSignedRankTestImpl.java
>>
>> 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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