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.ste...@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/surefire-reports. > You should be able to validate everything locally. > > > > I've also added a JIRA entry > https://issues.apache.org/jira/browse/MATH-814 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.developm...@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, 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 > >> > >> > > > > --------------------------------------------------------------------- > To unsubscribe, e-mail: dev-unsubscr...@commons.apache.org > For additional commands, e-mail: dev-h...@commons.apache.org > >
