[ https://issues.apache.org/jira/browse/MATH878?page=com.atlassian.jira.plugin.system.issuetabpanels:commenttabpanel&focusedCommentId=13474336#comment13474336
]
Ted Dunning commented on MATH878:

1. The array of convenience methods seems excessive. For instance, all that
{code}
boolean gTestGoodnessOfFit(final double[] expected, final long[] observed,
final double alpha)
{code}
adds is a single comparison against alpha.
2. For all the vast number of convenience routines, you don't include the 2 x 2 test that
returns a signed square root of G^2 where the sign indicates higher or lower frequency than
expected.
3. This doesn't seem to integrate into the Commons Math framework for this kind of 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
>
> 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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