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Radoslav Tsvetkov edited comment on MATH878 at 10/12/12 11:00 AM:

Thanks Ted for your interest and quick comments. :)
I added rootLogLikelihoodRatio as proposed by you using your code from mahout. I kept the
name as it is more commonly in use for this functionality.
On your comments:
1. Usually commons.math has more convenience methods. For example ChiSquare has much more.
As I'm your opinion and allowed myself to provide less. Concerning gTestGoodnessOfFit  let
not forget that majority of users are not interested at all at pValues and Gvalues, all
they want to know is: true or false (can they reject the null or not). ChiSquateTEst provides
exactly the same functionality and it is in commons since 1.2  so it seems a good thing.
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.
3. The GTests are fully integrated in the commons TestUtils framework as all other ChiSquarem,
Anova etc ... With this patch I added some more test cases.
On request.
Could you provide pls. some reference data for rootLogLikelihoodRatio test?
was (Author: rtsvet):
Added rootLogLikelihoodRatio as proposed by Ted Dunning and additional framework tests
> 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.patch, vcsdiff16294.patch, vcsdiff56368.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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