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/surefirereports.
You should be able to validate everything locally.
>
> I've also added a JIRA entry https://issues.apache.org/jira/browse/MATH814 and
> on the wishlist
> http://wiki.apache.org/commons/MathWishList#preview
>
> Will update once there is any progress :)
Thanks!
Phil
>
> Cheers
> Dev
> On Thu, Jul 5, 2012 at 10:24 PM, Devl Devel <devl.development@gmail.com>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
>> http://en.wikipedia.org/wiki/Kendall_tau_rank_correlation_coefficient however
>> the test implementation will follow that defined by "Handbook of
>> Parametric and Nonparametric Statistical Procedures, Fifth Edition, Page
>> 1393 Test 30, ISBN10: 1439858012  ISBN13: 9781439858011."
>>
>> 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(n1)/2)
>> where n(n1)/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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