0560813 20250326003558.320220907235959.9 1 s. P cav_un_epca*0560812978-90-73592-40-764-64BolognaCOMPSTAT and SDS2022 cav_un_auth*0345793 Kalina Jan UTIA-B Stochastická informatika Department of Stochastic Informatics SI SI Department of Stochastic Informatics Ústav teorie informace a automatizace AV ČR, v. v. i. http://www.compstat2022.org/docs/COMPSTAT2022_BoA.pdf?20220718212814 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 on whether a multivariate distribution with more than two dimensions is exchangeable or not. Multivariate permutation tests of exchangeability of multivariate distributions are proposed, which are based on the nonparametric combination methodology, i.e. on combining nonparametric 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. cav_un_auth*0435780 COMPSTAT 2022: International Conference on Computational Statistics / 24./ 20220823 20220826 Bologna http://www.compstat2022.org/index.php IT 2023 4 O 4o 20231122150744.8 PR RVO:67985807 https://hdl.handle.net/11104/0333592 S 2022 Soubory v repozitáři: 0560813.pdf SCOPUS PUBMED WOS cav_un_epca*0560812 Book of Abstracts COMPSTAT 2022 COMPSTAT and SDS 2022 Bologna 64 64 978-90-73592-40-7