[jira] Commented: (MATH-160) Chi-Square Test for Comparing two binned Data Sets
[ https://issues.apache.org/jira/browse/MATH-160?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel#action_12511356 ] Luc Maisonobe commented on MATH-160: The applied fix added new public methods to the interface. This is considered an incompatible API change by the clirr maven plugin which now fails when comparing with version 1.1. Should the next version been bumped to 2.0 ? Previous discussions on the version numbering missed the point with this issue. 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. -- This message is automatically generated by JIRA. - You can reply to this email to add a comment to the issue online. - To unsubscribe, e-mail: [EMAIL PROTECTED] For additional commands, e-mail: [EMAIL PROTECTED]
[jira] Commented: (MATH-160) Chi-Square Test for Comparing two binned Data Sets
[ https://issues.apache.org/jira/browse/MATH-160?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel#action_12503276 ] Phil Steitz commented on MATH-160: -- With the reference in the last comment replacing the reference in the patch, this looks OK to me. We also need test cases, ideally validated against R, another package or published results somewhere. Patches welcome! 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. -- This message is automatically generated by JIRA. - You can reply to this email to add a comment to the issue online. - To unsubscribe, e-mail: [EMAIL PROTECTED] For additional commands, e-mail: [EMAIL PROTECTED]
[jira] Commented: (MATH-160) Chi-Square Test for Comparing two binned Data Sets
[ http://issues.apache.org/jira/browse/MATH-160?page=comments#action_12445327 ] aeriform commented on MATH-160: --- Not sure if this would be good enough as I am not sure entirely what you need, but there is a reference to the normalized chi-squared in the following article on Issue 45 of Cytometry page 48: http://www3.interscience.wiley.com/cgi-bin/fulltext/85011154/PDFSTART Cytometry ISSN: 1097-0320 (Online) ISSN: 0196-4763 (Print) Published 2001 Wiley-Liss, Inc.† Cytometry 45:47-55 (2001) Probability Binning Comparison: A Metric for Quantitating Multivariate Distribution Differences This work is a US government work, and as such, is in the public domain in the United States of America. (pg. 47) Is a reference like this sufficient to develop code from? Chi-Square Test for Comparing two binned Data Sets -- Key: MATH-160 URL: http://issues.apache.org/jira/browse/MATH-160 Project: Commons Math Issue Type: New Feature Reporter: Matthias Hummel Priority: Minor 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. -- This message is automatically generated by JIRA. - If you think it was sent incorrectly contact one of the administrators: http://issues.apache.org/jira/secure/Administrators.jspa - For more information on JIRA, see: http://www.atlassian.com/software/jira - To unsubscribe, e-mail: [EMAIL PROTECTED] For additional commands, e-mail: [EMAIL PROTECTED]
[jira] Commented: (MATH-160) Chi-Square Test for Comparing two binned Data Sets
[ http://issues.apache.org/jira/browse/MATH-160?page=comments#action_12444161 ] Phil Steitz commented on MATH-160: -- You are both right - Luc is correct in pointing out that we cannot use code taken or translated from Numerical Recipes (NR), nor can we implement numerical algorithms unique to NR. What we always try to do is implement standard algorithms that are documented elsewhere (i.e., find another source beyond NR). I have not looked carefully at the patch yet, but it should not be hard to find documentation for ChiSquare computed as described above. Any suggestions for sources or comments on the patch itself would be appreciated. Chi-Square Test for Comparing two binned Data Sets -- Key: MATH-160 URL: http://issues.apache.org/jira/browse/MATH-160 Project: Commons Math Issue Type: New Feature Reporter: Matthias Hummel Priority: Minor 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. -- This message is automatically generated by JIRA. - If you think it was sent incorrectly contact one of the administrators: http://issues.apache.org/jira/secure/Administrators.jspa - For more information on JIRA, see: http://www.atlassian.com/software/jira - To unsubscribe, e-mail: [EMAIL PROTECTED] For additional commands, e-mail: [EMAIL PROTECTED]
[jira] Commented: (MATH-160) Chi-Square Test for Comparing two binned Data Sets
[ http://issues.apache.org/jira/browse/MATH-160?page=comments#action_12442869 ] Matthias Hummel commented on MATH-160: -- There is no problem with the code included. It is not copied from Numerical Recipes, but was developed independently. Nevertheless it is the only reference in English I know of that explains the mathematical background. Chi-Square Test for Comparing two binned Data Sets -- Key: MATH-160 URL: http://issues.apache.org/jira/browse/MATH-160 Project: Commons Math Issue Type: New Feature Reporter: Matthias Hummel Priority: Minor 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. -- This message is automatically generated by JIRA. - If you think it was sent incorrectly contact one of the administrators: http://issues.apache.org/jira/secure/Administrators.jspa - For more information on JIRA, see: http://www.atlassian.com/software/jira - To unsubscribe, e-mail: [EMAIL PROTECTED] For additional commands, e-mail: [EMAIL PROTECTED]
[jira] Commented: (MATH-160) Chi-Square Test for Comparing two binned Data Sets
[ http://issues.apache.org/jira/browse/MATH-160?page=comments#action_12442651 ] Luc Maisonobe commented on MATH-160: I'm affraid code from any of the Numerical Recipes book cannot be included in commons-math. See the redistribution conditions in the NR site here: http://www.numerical-recipes.com/infotop.html#distinfo If the code is a well known algorithm with public references independant from NR, then it is OK. But the comments in your patch directly references the NR book in C++. Of course, this only my point of view, could anybody else give an advice on this topic ? Chi-Square Test for Comparing two binned Data Sets -- Key: MATH-160 URL: http://issues.apache.org/jira/browse/MATH-160 Project: Commons Math Issue Type: New Feature Reporter: Matthias Hummel Priority: Minor 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. -- This message is automatically generated by JIRA. - If you think it was sent incorrectly contact one of the administrators: http://issues.apache.org/jira/secure/Administrators.jspa - For more information on JIRA, see: http://www.atlassian.com/software/jira - To unsubscribe, e-mail: [EMAIL PROTECTED] For additional commands, e-mail: [EMAIL PROTECTED]
