0476587 20240903170637.120170731235959.9 85026546598 000407667400006 10.14736/kyb-2017-3-0480 Directional quantile regression in R 13 s. P cav_un_epca*02971630023-5954Kybernetika533 (2017)480-492Ústav teorie informace a automatizace AV ČR, v. v. i. multivariate quantile regression quantile halfspace depth depth contour cav_un_auth*0101069 Boček Pavel Stochastická informatika Department of Stochastic Informatics SI SI UTIA-B Department of Stochastic Informatics Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0266474 Šiman Miroslav Stochastická informatika Department of Stochastic Informatics SI SI UTIA-B Department of Stochastic Informatics CZ Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2017/SI/bocek-0476587.pdf cav_un_auth*0307008 GA14-07234S GA ČR Recently, the eminently popular standard quantile regression has been generalized to the multiple-output regression setup by means of directional regression quantiles in two rather interrelated ways. Unfortunately, they lead to complicated optimization problems involving parametric programming, and this may be the main obstacle standing in the way of their wide dissemination. The presented R package modQR is intended to address this issue. It originates as a quite faithful translation of the authors' moQuantile toolbox for Octave and MATLAB, and provides all the necessary computational support for both the directional multiple-output quantile regression methods to the wide statistical public. The article offers a concise summary of the statistical theory behind modQR, overviews the package in brief, points out its departures from moQuantile, comments on its use and performance, and demonstrates its application. BD 10000 10100 10102 2018 2 RVO:67985556 http://hdl.handle.net/11104/0273538 S 3+4 Article Computer Science Cybernetics 3+4 Article Computer Science Cybernetics 3+4 Article Computer Science Cybernetics COMPUTERSCIENCE.CYBERNETICS 0.596 0.048 12.4 0.00096 0.224 808 0.321 0.513 63 Q4 18.907 11.4 Q4 Q3 0.2 Q4 11.364 2017 85026546598 SCOPUS PUBMED 000407667400006 WOS cav_un_epca*0297163 Kybernetika 0023-5954 Roč. 53 č. 3 2017 480 492 Ústav teorie informace a automatizace AV ČR, v. v. i.