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From rado tzvetkov <rtzvet...@yahoo.com>
Subject [math] G-Tests in math.stat.inference
Date Tue, 09 Oct 2012 11:53:49 GMT
Need for additional statistics hypothesis Tests in math.stat.inference

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-testsare tests that 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 whereObserved
>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. 


I estimate the implementation effort as relatively small as the implementation differs only
on few lines with the existing Chi-square tests.  

Also I already have code to contribute and tests for G-Test for independence. (if needed)
apache mahout also has some code implemented for LLR


best regards

Rado

P.S. Enhancing math.stat.inference with additional test could be generally good.    
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