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From Phil Steitz <>
Subject Re: [math] G-Tests in math.stat.inference
Date Tue, 09 Oct 2012 15:28:47 GMT
Thanks, Rado.  You are most welcome to open a JIRA ticket [1] and
attach code with references there.  I agree this would be a useful
addition to [math]. Thanks in advance.



On 10/9/12 4:53 AM, rado tzvetkov wrote:
> 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:
> 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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