Directional quantile regression in R

0476587 - ÚTIA 2018 RIV CZ eng J - Journal Article
Boček, Pavel - Šiman, Miroslav
Directional quantile regression in R.
Kybernetika. Roč. 53, č. 3 (2017), s. 480-492. ISSN 0023-5954
R&D Projects: GA ČR GA14-07234S
Institutional support: RVO:67985556
Keywords : multivariate quantile * regression quantile * halfspace depth * depth contour
OECD category: Applied mathematics
Impact factor: 0.632, year: 2017
http://library.utia.cas.cz/separaty/2017/SI/bocek-0476587.pdf

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.
Permanent Link: http://hdl.handle.net/11104/0273538