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Is there a multivariate alternative to two-sample Kolmogorov-Smirnov test? What I mean is a test that can be used to check whenever two underlying multidimensional distributions differ.

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A 2004 article On a new multivariate two-sample test by Baringhaus and Franz maybe helpful, they provided a brief literature review on the two-sample multivariate GoF tests and then a R package cramer. As the package name suggested their method is related to Cramer's test, a predecessor of Cramer-von Mises.

For one-sample problem Justel et al. developed a generalization of Kolmogorov-Smirnov test. In general it seems the difficulty in multivariate case rooted from extending the definition of EDF (empirical distribution function), so methods based on other measures are worth exploring, e.g. multivariate tests based on ECF (empirical characteristic function) by Fan.

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  • $\begingroup$ Please spell out abbrevs EDF, ECF $\endgroup$ – kjetil b halvorsen Apr 13 '17 at 22:24
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    $\begingroup$ @kjetilbhalvorsen: fixed, though it's quite clear what they are once click the links provided. $\endgroup$ – Francis Apr 13 '17 at 23:00

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