0583622 20240527122713.020240305235959.9 85066100659 000469602900001 10.1080/03610918.2019.1615624 13 s. P cav_un_epca*02564340361-09185010 (2021)2845-2857Taylor & Francis multivariate estimation symmetry test robust estimation scatter estimator axial symmetry 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. https://www.tandfonline.com/doi/full/10.1080/03610918.2019.1615624 http://library.utia.cas.cz/separaty/2024/SI/kalina-0583622.pdf GA17-07384S GA ČR cav_un_auth*0345381 The article discusses how various multivariate location and scatter estimators capture the symmetry of the underlying distribution. Very general sufficient conditions are formulated, which ensure various symmetry properties of functionals corresponding to location or scatter. Examples of robust multivariate estimators, which fulfill these conditions, are discussed in detail. The obtained symmetry of the estimators is applicable to hypothesis tests of symmetry of the underlying distribution of the multivariate data. For this task, we propose to perform permutation tests exploiting the nonparametric combination methodology. The performance of the newly proposed tests is illustrated on simulated as well as real data. The tests are suitable for small sample sizes and represent the first available symmetry tests suitable also for non-elliptical distributions and for more than just two variables. WOS BB 10000 10100 10103 2024 RVO:67985556 https://hdl.handle.net/11104/0351629 S 2 Article Statistics Probability C STATISTICS&PROBABILITY 1.105 0.459 6.9 0.00515 0.316 4683 60 0.419 27.21 1 702 Q3 0.997 579 Q3 27.6 Q4 Q4 0.48 Q3 27.6 2021 85066100659 SCOPUS PUBMED 000469602900001 WOS cav_un_epca*0256434 Communications in Statistics - Simulation and Computation Roč. 50 č. 10 2021 2845 2857 0361-0918 1532-4141 Taylor & Francis