| bibtype |
J -
Journal Article
|
| ARLID |
0583578 |
| utime |
20240527122908.8 |
| mtime |
20240305235959.9 |
| SCOPUS |
85134794382 |
| WOS |
000830637300001 |
| DOI |
10.1080/02664763.2022.2102158 |
| title
(primary) (eng) |
Testing exchangeability of multivariate distributions |
| specification |
| page_count |
15 s. |
| media_type |
P |
|
| serial |
| ARLID |
cav_un_epca*0253572 |
| ISSN |
0266-4763 |
| title
|
Journal of Applied Statistics |
| volume_id |
50 |
| volume |
15 (2023) |
| page_num |
3142-3156 |
| publisher |
|
|
| keyword |
multivariate distribution |
| keyword |
exchangeable distribution |
| keyword |
multivariate permutation test |
| keyword |
multiple testing |
| keyword |
non-parametric combination methodology |
| keyword |
multiple comparisons |
| author
(primary) |
| ARLID |
cav_un_auth*0345793 |
| name1 |
Kalina |
| name2 |
Jan |
| institution |
UTIA-B |
| full_dept (cz) |
Stochastická informatika |
| full_dept (eng) |
Department of Stochastic Informatics |
| department (cz) |
SI |
| department (eng) |
SI |
| full_dept |
Department of Stochastic Informatics |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0435779 |
| name1 |
Janáček |
| name2 |
P. |
| country |
CZ |
|
| source |
|
| source |
|
| cas_special |
| project |
| project_id |
GA21-05325S |
| agency |
GA ČR |
| ARLID |
cav_un_auth*0409039 |
|
| project |
| project_id |
GA22-02067S |
| agency |
GA ČR |
| country |
CZ |
| ARLID |
cav_un_auth*0435776 |
|
| abstract
(eng) |
lthough there have been a number of available tests of bivariate exchangeability, i.e. bivariate symmetry for bivariate distributions, the literature is void of tests whether a multivariate distribution with more than two dimensions is exchangeable or not. In this paper, multivariate permutation tests of exchangeability of multivariate distributions are proposed, which are based on the non-parametric combination methodology, i.e. on combining non-parametric bivariate exchangeability tests. Numerical experiments on real as well as simulated multivariate data with more than two dimensions are presented here. The multivariate permutation test turns out to be typically more powerful than a bivariate exchangeability test performed only over a single pair of variables, and also more suitable compared to tests exploiting the approaches of Benjamini–Yekutieli or Bonferroni. |
| result_subspec |
WOS |
| RIV |
BB |
| FORD0 |
10000 |
| FORD1 |
10100 |
| FORD2 |
10103 |
| reportyear |
2024 |
| inst_support |
RVO:67985556 |
| permalink |
https://hdl.handle.net/11104/0351584 |
| confidential |
S |
| mrcbC91 |
A |
| mrcbT16-e |
STATISTICSPROBABILITY |
| mrcbT16-j |
0.483 |
| mrcbT16-s |
0.545 |
| mrcbT16-D |
Q4 |
| mrcbT16-E |
Q3 |
| arlyear |
2023 |
| mrcbU14 |
85134794382 SCOPUS |
| mrcbU24 |
PUBMED |
| mrcbU34 |
000830637300001 WOS |
| mrcbU63 |
cav_un_epca*0253572 Journal of Applied Statistics Roč. 50 č. 15 2023 3142 3156 0266-4763 1360-0532 Taylor & Francis |
|