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https://issues.apache.org/jira/browse/MATH-160?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Phil Steitz resolved MATH-160.
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Resolution: Fixed
Applied a modified version of the patch, along with test cases, verified
against DATAPLOT
Modifications:
* Changed input array data type to long[]. This is consistent with other
ChiSquare tests and with the specification of the test (i.e., it is not clear
what floats as arguments would mean)
* Added weighting as specified in the NIST reference provided to adjust for
possibly different bin sums for the two samples.
> Chi-Square Test for Comparing two binned Data Sets
> --------------------------------------------------
>
> Key: MATH-160
> URL: https://issues.apache.org/jira/browse/MATH-160
> Project: Commons Math
> Issue Type: New Feature
> Reporter: Matthias Hummel
> Priority: Minor
> Fix For: 1.2
>
> Attachments: commons-math.patch
>
>
> Current Chi-Square test implementation only supports standard Chi-Square
> testing with respect to known distribution. We needed testing for comparison
> of two sample data sets where the distribution can be unknown. For this case
> the Chi-Square test has to be computed in a different way so that both error
> contributions (one for each sample data set) are taken into account. See
> Press et. al, Numerical Recipes, Second Edition, formula 14.3.2.
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