| bibtype |
J -
Journal Article
|
| ARLID |
0476587 |
| utime |
20240903170637.1 |
| mtime |
20170731235959.9 |
| SCOPUS |
85026546598 |
| WOS |
000407667400006 |
| DOI |
10.14736/kyb-2017-3-0480 |
| title
(primary) (eng) |
Directional quantile regression in R |
| specification |
| page_count |
13 s. |
| media_type |
P |
|
| serial |
| ARLID |
cav_un_epca*0297163 |
| ISSN |
0023-5954 |
| title
|
Kybernetika |
| volume_id |
53 |
| volume |
3 (2017) |
| page_num |
480-492 |
| publisher |
| name |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
|
| keyword |
multivariate quantile |
| keyword |
regression quantile |
| keyword |
halfspace depth |
| keyword |
depth contour |
| author
(primary) |
| ARLID |
cav_un_auth*0101069 |
| name1 |
Boček |
| name2 |
Pavel |
| full_dept (cz) |
Stochastická informatika |
| full_dept (eng) |
Department of Stochastic Informatics |
| department (cz) |
SI |
| department (eng) |
SI |
| institution |
UTIA-B |
| full_dept |
Department of Stochastic Informatics |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0266474 |
| name1 |
Šiman |
| name2 |
Miroslav |
| full_dept (cz) |
Stochastická informatika |
| full_dept |
Department of Stochastic Informatics |
| department (cz) |
SI |
| department |
SI |
| institution |
UTIA-B |
| full_dept |
Department of Stochastic Informatics |
| country |
CZ |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| source |
|
| cas_special |
| project |
| ARLID |
cav_un_auth*0307008 |
| project_id |
GA14-07234S |
| agency |
GA ČR |
|
| abstract
(eng) |
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. |
| RIV |
BD |
| FORD0 |
10000 |
| FORD1 |
10100 |
| FORD2 |
10102 |
| reportyear |
2018 |
| num_of_auth |
2 |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0273538 |
| confidential |
S |
| mrcbC86 |
3+4 Article Computer Science Cybernetics |
| mrcbC86 |
3+4 Article Computer Science Cybernetics |
| mrcbC86 |
3+4 Article Computer Science Cybernetics |
| mrcbT16-e |
COMPUTERSCIENCECYBERNETICS |
| mrcbT16-j |
0.224 |
| mrcbT16-s |
0.321 |
| mrcbT16-B |
18.907 |
| mrcbT16-D |
Q4 |
| mrcbT16-E |
Q3 |
| arlyear |
2017 |
| mrcbU14 |
85026546598 SCOPUS |
| mrcbU24 |
PUBMED |
| mrcbU34 |
000407667400006 WOS |
| mrcbU63 |
cav_un_epca*0297163 Kybernetika 0023-5954 Roč. 53 č. 3 2017 480 492 Ústav teorie informace a automatizace AV ČR, v. v. i. |
|