| bibtype |
J -
Journal Article
|
| ARLID |
0446857 |
| utime |
20240103210501.5 |
| mtime |
20150904235959.9 |
| WOS |
000356993100007 |
| SCOPUS |
84938592517 |
| DOI |
10.3150/14-BEJ610 |
| title
(primary) (eng) |
Local bilinear multiple-output quantile/depth regression |
| specification |
| page_count |
32 s. |
| media_type |
P |
|
| serial |
| ARLID |
cav_un_epca*0252218 |
| ISSN |
1350-7265 |
| title
|
Bernoulli |
| volume_id |
21 |
| volume |
3 (2015) |
| page_num |
1435-1466 |
| publisher |
| name |
International Statistical Institute |
|
|
| keyword |
conditional depth |
| keyword |
growth chart |
| keyword |
halfspace depth |
| keyword |
local bilinear regression |
| keyword |
multivariate quantile |
| keyword |
quantile regression |
| keyword |
regression depth |
| author
(primary) |
| ARLID |
cav_un_auth*0280802 |
| name1 |
Hallin |
| name2 |
M. |
| country |
BE |
|
| author
|
| ARLID |
cav_un_auth*0319159 |
| name1 |
Lu |
| name2 |
Z. |
| country |
GB |
|
| author
|
| 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 |
|
| abstract
(eng) |
A new quantile regression concept, based on a directional version of Koenker and Bassett's traditional single-output one, has been introduced in [Ann. Statist. (2010) 38 635-669] for multiple-output location/linear regression problems. The polyhedral contours provided by the empirical counterpart of that concept, however, cannot adapt to unknown nonlinear and/or heteroskedastic dependencies. This paper therefore introduces local constant and local linear (actually, bilinear) versions of those contours, which both allow to asymptotically recover the conditional halfspace depth contours that completely characterize the response's conditional distributions. Bahadur representation and asymptotic normality results are established. Illustrations are provided both on simulated and real data. |
| reportyear |
2016 |
| RIV |
BA |
| mrcbC52 |
4 A hod 4ah 20231122141116.4 |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0248946 |
| cooperation |
| ARLID |
cav_un_auth*0319160 |
| name |
Universite libre de Bruxelles |
| country |
BE |
|
| cooperation |
| ARLID |
cav_un_auth*0309080 |
| name |
Princeton University |
| country |
US |
|
| cooperation |
| ARLID |
cav_un_auth*0319161 |
| name |
University of Southampton |
| country |
GB |
|
| mrcbC64 |
1 Department of Stochastic Informatics UTIA-B 10103 STATISTICS & PROBABILITY |
| confidential |
S |
| mrcbT16-e |
STATISTICSPROBABILITY |
| mrcbT16-j |
1.692 |
| mrcbT16-s |
2.115 |
| mrcbT16-4 |
Q1 |
| mrcbT16-B |
81.674 |
| mrcbT16-C |
70.325 |
| mrcbT16-D |
Q1 |
| mrcbT16-E |
Q1 |
| arlyear |
2015 |
| mrcbTft |
\nSoubory v repozitáři: siman-0446857.pdf |
| mrcbU14 |
84938592517 SCOPUS |
| mrcbU34 |
000356993100007 WOS |
| mrcbU63 |
cav_un_epca*0252218 Bernoulli 1350-7265 1573-9759 Roč. 21 č. 3 2015 1435 1466 International Statistical Institute |
|