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Title: Directional quantile regression in R (English)
Author: Boček, Pavel
Author: Šiman, Miroslav
Language: English
Journal: Kybernetika
ISSN: 0023-5954 (print)
ISSN: 1805-949X (online)
Volume: 53
Issue: 3
Year: 2017
Pages: 480-492
Summary lang: English
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Category: math
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Summary: 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. (English)
Keyword: multivariate quantile
Keyword: regression quantile
Keyword: halfspace depth
Keyword: regression depth
Keyword: depth contour
MSC: 62-04
MSC: 62H05
MSC: 62J99
MSC: 65C60
idZBL: Zbl 06819619
idMR: MR3684681
DOI: 10.14736/kyb-2017-3-0480
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Date available: 2017-11-12T09:44:17Z
Last updated: 2018-01-10
Stable URL: http://hdl.handle.net/10338.dmlcz/146938
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