Testing Exchangeability of Multivariate Distributions

0559538 - ÚI 2024 RIV GB eng J - Journal Article
Kalina, Jan - Janáček, Patrik
Testing Exchangeability of Multivariate Distributions.
Journal of Applied Statistics. Roč. 50, č. 15 (2023), s. 3142-3156. ISSN 0266-4763. E-ISSN 1360-0532
R&D Projects: GA ČR GA21-05325S; GA ČR(CZ) GA22-02067S
Institutional support: RVO:67985807
Keywords : multivariate distribution * exchangeable distribution * multivariate permutation test * multiple testing * non-parametric combination methodology * multiple comparisons
OECD category: Statistics and probability
Impact factor: 1.5, year: 2022
Method of publishing: Open access
https://dx.doi.org/10.1080/02664763.2022.2102158

Although there have been a number of available tests of bivariate exchangeability, i.e. bivariate symmetry for bivariate distributions, the literature is void of tests whether a multivariate distribution with more than two dimensions is exchangeable or not. In this paper, multivariate permutation tests of exchangeability of multivariate distributions are proposed, which are based on the non-parametric combination methodology, i.e. on combining non-parametric bivariate exchangeability tests. Numerical experiments on real as well as simulated multivariate data with more than two dimensions are presented here. The multivariate permutation test turns out to be typically more powerful than a bivariate exchangeability test performed only over a single pair of variables, and also more suitable compared to tests exploiting the approaches of Benjamini–Yekutieli or Bonferroni.
Permanent Link: https://hdl.handle.net/11104/0332806