Beyond two-sample-tests: Localizing data discrepancies in high-dimensional spaces

Abstract

Comparing two sets of multivariate samples is a central problem in data analysis. From a statistical standpoint, the simplest way to perform such a comparison is to resort to a non-parametric two-sample test (TST), which checks whether the two sets can be seen as i.i.d. samples of an identical unknown distribution (the null hypothesis). If the null is… (More)
DOI: 10.1109/DSAA.2015.7344835

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