Hi Phil
I took a closer look at the Spearmans correlation and note that it uses an
underlying PearsonsCorrelation object to do the actual work of calculating
the correlation value after ranking.
Do I have to do the same for Kendalls Tau? I.e. Do I need to have two
classes 1)KendallsTauCorrelation which is the equiv of SpearmansCorrelation
and then say KendallsTauComputation which is the equivilant of
PearsonsCorrelation? Of can I just put everything into one class called
KendallsTauCorrelation which does the ranking using the RankingAlgorithm
interface *and* tau computation all in one class?
Hope that makes sense?
Cheers
Dev
On Tue, Jul 10, 2012 at 10:10 PM, Phil Steitz <phil.steitz@gmail.com> wrote:
> 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_coefficienthowever
> >> 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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