alternatives to KS test applicable to K-samples
Thanks for your insight, David But I am not interested in comparing means among multiple groups. Instead, I want to compare empirical distributions. In this case, I am not sure if wilcoxon should be still applicable. still appreciate it.
On Fri, May 29, 2015 at 1:32 PM, David Winsemius <dwinsemius at comcast.net> wrote:
On May 29, 2015, at 9:31 AM, Wensui Liu wrote:
Good morning, All I have a stat question not specifically related to the the programming language. To compare distributional consistency / discrepancy between two samples, we usually use kolmogorov-smirnov test, which is implemented in R with ks.test() or in SAS with "pro npar1way edf". I am wondering if there is any alternative to KS test that could be generalized to K-samples.
The 'coin' package (Hothorn, Hornick, van de Weil, and Zeileis) presents a variety of permutation and rank-based tests that would probably be more powerful than any multi-group variant of the KS test. The multi-group variant of the Wilcoxon Rank Sum Test presented in the examples for the help page: ?wilcox_test is the Nemenyi-Damico-Wolfe-Dunn test. -- David Winsemius Alameda, CA, USA
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