| bibtype |
J -
Journal Article
|
| ARLID |
0376413 |
| utime |
20240103200824.9 |
| mtime |
20120511235959.9 |
| WOS |
000301214900008 |
| DOI |
10.1016/j.csda.2010.11.014 |
| title
(primary) (eng) |
Computing multiple-output regression quantile regions |
| specification |
|
| serial |
| ARLID |
cav_un_epca*0256439 |
| ISSN |
0167-9473 |
| title
|
Computational Statistics and Data Analysis |
| volume_id |
56 |
| volume |
4 (2012) |
| page_num |
840-853 |
| publisher |
|
|
| keyword |
halfspace depth |
| keyword |
multiple-output regression |
| keyword |
parametric linear programming |
| keyword |
quantile regression |
| author
(primary) |
| ARLID |
cav_un_auth*0274302 |
| name1 |
Paindaveine |
| name2 |
D. |
| country |
BE |
|
| 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 |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| source |
|
| cas_special |
| project |
| project_id |
1M06047 |
| agency |
GA MŠk |
| country |
CZ |
| ARLID |
cav_un_auth*0217941 |
|
| research |
CEZ:AV0Z10750506 |
| abstract
(eng) |
A procedure relying on linear programming techniques is developed to compute (regression) quantile regions that have been defined recently. In the location case, this procedure allows for computing halfspace depth regions even beyond dimension two. The corresponding algorithm is described in detail, and illustrations are provided both for simulated and real data. The efficiency of a Matlab implementation of the algorithm is also investigated through extensive simulations. |
| reportyear |
2013 |
| RIV |
BA |
| permalink |
http://hdl.handle.net/11104/0208819 |
| mrcbT16-e |
COMPUTERSCIENCEINTERDISCIPLINARYAPPLICATIONS|STATISTICSPROBABILITY |
| mrcbT16-f |
1.449 |
| mrcbT16-g |
0.415 |
| mrcbT16-h |
5.8 |
| mrcbT16-i |
0.02601 |
| mrcbT16-j |
0.917 |
| mrcbT16-k |
4718 |
| mrcbT16-l |
325 |
| mrcbT16-q |
51 |
| mrcbT16-s |
1.277 |
| mrcbT16-y |
26.07 |
| mrcbT16-x |
1.4 |
| mrcbT16-4 |
Q1 |
| mrcbT16-B |
68.868 |
| mrcbT16-C |
60.006 |
| mrcbT16-D |
Q2 |
| mrcbT16-E |
Q2 |
| arlyear |
2012 |
| mrcbU34 |
000301214900008 WOS |
| mrcbU63 |
cav_un_epca*0256439 Computational Statistics and Data Analysis 0167-9473 1872-7352 Roč. 56 č. 4 2012 840 853 Elsevier |
|