0481224 20240103214926.020171112235959.9 85024472119 000438753900017 10.1080/03610918.2017.1337136 13 s. P cav_un_epca*02564340361-0918477 (2018)2139-2151Taylor & Francis Breakdown point Estimators Geometric median Location Trimmed mean cav_un_auth*0309054 Adam Lukáš Matematická teorie rozhodování Department of Decision Making Theory MTR MTR UTIA-B Department of Decision Making Theory CZ Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0353596 Bejda P. CZ http://library.utia.cas.cz/separaty/2017/MTR/adam-0481224.pdf In this article, we propose new estimators of location. These estimators select a robust set around the geometric median, enlarge it, and compute the (iterative) weighted mean from it. By doing so, we obtain a robust estimator in the sense of the breakdown point, which uses more observations than standard estimators. We apply our approach on the concepts of boxplot and bagplot. We work in a general normed vector space and allow multi-valued estimators. BA 10000 10100 10101 2019 2 RVO:67985556 http://hdl.handle.net/11104/0277007 cav_un_auth*0296304 Matematicko-fyzikální fakulta KU MFF KU CZ S 3+4 Article Statistics Probability STATISTICS&PROBABILITY 0.555 0.194 9.1 0.00354 0.213 1989 0.398 0.448 201 Q4 8.453 6.9 Q4 Q4 0.37 Q3 6.911 2018 85024472119 SCOPUS PUBMED 000438753900017 WOS cav_un_epca*0256434 Communications in Statistics - Simulation and Computation 0361-0918 1532-4141 Roč. 47 č. 7 2018 2139 2151 Taylor & Francis