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From Phil Steitz <>
Subject Re: [math] Kendall's Tau Implementation
Date Tue, 10 Jul 2012 21:10:02 GMT
On 7/10/12 12:09 PM, Devl Devel wrote:
> Hi Phil and All.
> Thanks for the welcome. I manage to get,build and test the SVN trunk branch
> and took a look at the Spearmans Rank implementation. I did notice a few
> test failures overall in the build such as RealVectorTest, hopefully they
> are part of the build and not something I am missing in my checkout.

Don't worry about the RealVector test failures, that is a known
issue that will hopefully soon be resolved.
> My only question for now is: how can I view the Jenkins build to see what's
> not passing tests at the moment? I understand there are email alerts
> however it would be good to see (readonly) the state of the current build
> somehow.

You can see the test output locally in /target/surefire-reports. 
You should be able to validate everything locally.
> I've also added a JIRA entry and
> on the wishlist
> Will update once there is any progress :)


> Cheers
> Dev
> On Thu, Jul 5, 2012 at 10:24 PM, Devl Devel <>wrote:
>> Hi All,
>> Below is a proposal for a new feature:
>> *A concise description of the new feature / enhancement*
>> *
>> *
>> I propose a new feature to implement the Kendall's Tau which is a measure
>> of Association/Correlation between ranked ordinal data.
>> *References to definitions and algorithms.*
>> *
>> *A basic description is available at
>> however
>> the test implementation will follow that defined by "Handbook of
>> Parametric and Nonparametric Statistical Procedures, Fifth Edition, Page
>> 1393 Test 30, ISBN-10: 1439858012 | ISBN-13: 978-1439858011."
>> The algorithm is proposed as follows.
>> Given two rankings or permutations represented by a 2D matrix; columns
>> indicate rankings (e.g. by an individual) and row are observations of each
>> rank. The algorithm is to calculate the total number of concordant pairs of
>> ranks (between columns), discordant pairs of ranks  (between columns) and
>> calculate the Tau defined as
>> tau= (Number of concordant - number of discordant)/(n(n-1)/2)
>>  where n(n-1)/2 is the total number of possible pairs of ranks.
>> The method will then output the tau value between 0 and 1 where 1
>> signifies a "perfect" correlation between the two ranked lists.
>> Where ties exist within a ranking it is marked as neither concordant nor
>> discordant in the calculation. An optional merge sort can be used to speed
>> up the implementation. Details are in the wiki page.
>> *Some indication of why the addition / enhancement is practically useful*
>> *
>> *
>> Although this implementation is not particularly complex it would be
>> useful to have it in a consistent format in the commons math package in
>> addition to existing correlation tests. Kendall's Tau is used effectively
>> in comparing ranks for products, rankings from search engines or
>> measurements from engineering equipment.
>> This  is my first post on this list, I tried to follow the guidelines but
>> let me know if I need to elaborate.
>> Regards
>> Dev

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