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https://issues.apache.org/jira/browse/MATH-878?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Phil Steitz resolved MATH-878.
------------------------------
Resolution: Fixed
In r1408172, I changed method names to match the conventions of the other
classes in the inference package: g() returns the g stat, gTest does tests,
etc. I added G-test statistics to TestUtils in r1408173 and updated the user
guide in r1408174.
Thanks again for the patch.
> G-Test (Log-Likelihood ratio - LLR test) in math.stat.inference
> ---------------------------------------------------------------
>
> Key: MATH-878
> URL: https://issues.apache.org/jira/browse/MATH-878
> Project: Commons Math
> Issue Type: New Feature
> Environment: Netbeans
> Reporter: Radoslav Tsvetkov
> Labels: features, test
> Fix For: 3.1
>
> Attachments: MATH-878_gTest_12102012.patch,
> MATH-878_gTest_15102012.patch, MATH-878_gTest_26102012.patch,
> vcs-diff16294.patch
>
> Original Estimate: 24h
> Remaining Estimate: 24h
>
> 1. Implementation of G-Test (Log-Likelihood ratio LLR test for independence
> and goodnes-of-fit)
> 2. Reference: http://en.wikipedia.org/wiki/G-test
> 3. Reasons-Usefulness: G-tests are tests are increasingly being used in
> situations where chi-squared tests were previously recommended.
> The approximation to the theoretical chi-squared distribution for the G-test
> is better than for the Pearson chi-squared tests. In cases where Observed
> >2*Expected for some cell case, the G-test is always better than the
> chi-squared test.
> For testing goodness-of-fit the G-test 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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