| bibtype |
J -
Journal Article
|
| ARLID |
0458243 |
| utime |
20240103212108.5 |
| mtime |
20160415235959.9 |
| WOS |
000367862500031 |
| SCOPUS |
84960447026 |
| DOI |
10.1016/j.spl.2015.11.021 |
| title
(primary) (eng) |
Elliptical multiple-output quantile regression and convex optimization |
| specification |
| page_count |
6 s. |
| media_type |
P |
|
| serial |
| ARLID |
cav_un_epca*0257616 |
| ISSN |
0167-7152 |
| title
|
Statistics & Probability Letters |
| volume_id |
109 |
| volume |
1 (2016) |
| page_num |
232-237 |
| publisher |
|
|
| keyword |
quantile regression |
| keyword |
elliptical quantile |
| keyword |
multivariate quantile |
| keyword |
multiple-output regression |
| author
(primary) |
| ARLID |
cav_un_auth*0280802 |
| name1 |
Hallin |
| name2 |
M. |
| 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 |
GA14-07234S |
| agency |
GA ČR |
| ARLID |
cav_un_auth*0307008 |
|
| abstract
(eng) |
This article extends linear quantile regression to an elliptical multiple-output regression setup. The definition of the proposed concept leads to a convex optimization problem. Its elementary properties, and the consistency of its sample counterpart, are investigated. An empirical application is provided. |
| reportyear |
2017 |
| RIV |
BA |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0258934 |
| cooperation |
| ARLID |
cav_un_auth*0319160 |
| institution |
ULB |
| name |
Universite libre de Bruxelles |
| country |
BE |
|
| confidential |
S |
| mrcbC86 |
3+4 Article Statistics Probability |
| mrcbT16-e |
STATISTICS&PROBABILITY |
| mrcbT16-f |
0.636 |
| mrcbT16-g |
0.1 |
| mrcbT16-h |
9.7 |
| mrcbT16-i |
0.0105 |
| mrcbT16-j |
0.455 |
| mrcbT16-k |
3769 |
| mrcbT16-s |
0.694 |
| mrcbT16-4 |
Q2 |
| mrcbT16-5 |
0.455 |
| mrcbT16-6 |
280 |
| mrcbT16-7 |
Q4 |
| mrcbT16-B |
22.701 |
| mrcbT16-C |
19.8 |
| mrcbT16-D |
Q4 |
| mrcbT16-E |
Q3 |
| mrcbT16-P |
19.758 |
| arlyear |
2016 |
| mrcbU14 |
84960447026 SCOPUS |
| mrcbU34 |
000367862500031 WOS |
| mrcbU63 |
cav_un_epca*0257616 Statistics & Probability Letters 0167-7152 1879-2103 Roč. 109 č. 1 2016 232 237 Elsevier |
|