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Radoslav Tsvetkov commented on MATH878:

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?
> 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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