On Wasserstein Two-Sample Testing and Related Families of Nonparametric Tests
AbstractNonparametric two-sample or homogeneity testing is a decision theoretic problem that involves identifying differences between two random variables without making parametric assumptions about their underlying distributions. The literature is old and rich, with a wide variety of statistics having being designed and analyzed, both for the unidimensional and the multivariate setting. In this short survey, we focus on test statistics that involve the Wasserstein distance. Using an entropic smoothing of the Wasserstein distance, we connect these to very different tests including multivariate methods involving energy statistics and kernel based maximum mean discrepancy and univariate methods like the Kolmogorov–Smirnov test, probability or quantile (PP/QQ) plots and receiver operating characteristic or ordinal dominance (ROC/ODC) curves. Some observations are implicit in the literature, while others seem to have not been noticed thus far. Given nonparametric two-sample testing’s classical and continued importance, we aim to provide useful connections for theorists and practitioners familiar with one subset of methods but not others. View Full-Text
Scifeed alert for new publicationsNever miss any articles matching your research from any publisher
- Get alerts for new papers matching your research
- Find out the new papers from selected authors
- Updated daily for 49'000+ journals and 6000+ publishers
- Define your Scifeed now
Ramdas, A.; Trillos, N.G.; Cuturi, M. On Wasserstein Two-Sample Testing and Related Families of Nonparametric Tests. Entropy 2017, 19, 47.
Ramdas A, Trillos NG, Cuturi M. On Wasserstein Two-Sample Testing and Related Families of Nonparametric Tests. Entropy. 2017; 19(2):47.Chicago/Turabian Style
Ramdas, Aaditya; Trillos, Nicolás G.; Cuturi, Marco. 2017. "On Wasserstein Two-Sample Testing and Related Families of Nonparametric Tests." Entropy 19, no. 2: 47.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.