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Ted Dunning commented on MATH878:

{quote}
2. I added rootLogLikelihoodRatio using your code from mahout. Could you help me with the
rationale description comments. Unfortunately the quoted discussion is no longer available
in internet. I'll be better perhaps add some info inline in the comments.
{quote}
There is some more permanent discussion on the root LLR test here:
http://mailarchives.apache.org/mod_mbox/mahoutuser/201001.mbox/%3Cc7d45fc71001121120r6b0482aat345014770ed32744@mail.gmail.com%3E
And see the response to Wataru's comment here:
http://tdunning.blogspot.com/2008/03/surpriseandcoincidence.html
If I can squeeze some time, I will write you some purposebuilt rationale text, but you should
be able to lift some of my other comments with small changes.
> GTest (LogLikelihood ratio  LLR test) in math.stat.inference
> 
>
> Key: MATH878
> URL: https://issues.apache.org/jira/browse/MATH878
> Project: Commons Math
> Issue Type: New Feature
> Affects Versions: 3.1, 3.2, 4.0
> Environment: Netbeans
> Reporter: Radoslav Tsvetkov
> Labels: features, test
> Fix For: 3.1
>
> Attachments: MATH878_gTest_12102012.patch, MATH878_gTest.patch, vcsdiff16294.patch
>
> Original Estimate: 24h
> Remaining Estimate: 24h
>
> 1. Implementation of GTest (LogLikelihood ratio LLR test for independence and goodnesoffit)
> 2. Reference: http://en.wikipedia.org/wiki/Gtest
> 3. ReasonsUsefulness: Gtests are tests are increasingly being used in situations where
chisquared tests were previously recommended.
> The approximation to the theoretical chisquared distribution for the Gtest is better
than for the Pearson chisquared tests. In cases where Observed >2*Expected for some cell
case, the Gtest is always better than the chisquared test.
> For testing goodnessoffit the Gtest is infinitely more efficient than the chi squared
test in the sense of Bahadur, but the two tests are equally efficient in the sense of Pitman
or in the sense of Hodge and Lehman.

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