0458243 20240103212108.520160415235959.9 000367862500031 84960447026 10.1016/j.spl.2015.11.021 6 s. P cav_un_epca*02576160167-71521091 (2016)232-237Elsevier quantile regression elliptical quantile multivariate quantile multiple-output regression cav_un_auth*0280802 Hallin M. BE cav_un_auth*0266474 Šiman Miroslav Stochastická informatika Department of Stochastic Informatics SI SI UTIA-B Department of Stochastic Informatics Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2016/SI/siman-0458243.pdf GA14-07234S GA ČR cav_un_auth*0307008 This article extends linear quantile regression to an elliptical multiple-output regression setup. The definition of the proposed concept leads to a convex optimization problem. Its elementary properties, and the consistency of its sample counterpart, are investigated. An empirical application is provided. 2017 BA RVO:67985556 http://hdl.handle.net/11104/0258934 cav_un_auth*0319160 ULB Universite libre de Bruxelles BE S 3+4 Article Statistics Probability STATISTICS&PROBABILITY 0.636 0.1 9.7 0.0105 0.455 3769 0.694 Q2 0.455 280 Q4 22.701 19.8 Q4 Q3 19.758 2016 84960447026 SCOPUS 000367862500031 WOS cav_un_epca*0257616 Statistics & Probability Letters 0167-7152 1879-2103 Roč. 109 č. 1 2016 232 237 Elsevier