| bibtype |
J -
Journal Article
|
| ARLID |
0481224 |
| utime |
20240103214926.0 |
| mtime |
20171112235959.9 |
| SCOPUS |
85024472119 |
| WOS |
000438753900017 |
| DOI |
10.1080/03610918.2017.1337136 |
| title
(primary) (eng) |
Robust estimators based on generalization of trimmed mean |
| specification |
| page_count |
13 s. |
| media_type |
P |
|
| serial |
| ARLID |
cav_un_epca*0256434 |
| ISSN |
0361-0918 |
| title
|
Communications in Statistics - Simulation and Computation |
| volume_id |
47 |
| volume |
7 (2018) |
| page_num |
2139-2151 |
| publisher |
|
|
| keyword |
Breakdown point |
| keyword |
Estimators |
| keyword |
Geometric median |
| keyword |
Location |
| keyword |
Trimmed mean |
| author
(primary) |
| ARLID |
cav_un_auth*0309054 |
| name1 |
Adam |
| name2 |
Lukáš |
| full_dept (cz) |
Matematická teorie rozhodování |
| full_dept (eng) |
Department of Decision Making Theory |
| department (cz) |
MTR |
| department (eng) |
MTR |
| institution |
UTIA-B |
| full_dept |
Department of Decision Making Theory |
| country |
CZ |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0353596 |
| name1 |
Bejda |
| name2 |
P. |
| country |
CZ |
|
| source |
|
| cas_special |
| abstract
(eng) |
In this article, we propose new estimators of location. These estimators select a robust set around the geometric median, enlarge it, and compute the (iterative) weighted mean from it. By doing so, we obtain a robust estimator in the sense of the breakdown point, which uses more observations than standard estimators. We apply our approach on the concepts of boxplot and bagplot. We work in a general normed vector space and allow multi-valued estimators. |
| RIV |
BA |
| FORD0 |
10000 |
| FORD1 |
10100 |
| FORD2 |
10101 |
| reportyear |
2019 |
| num_of_auth |
2 |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0277007 |
| cooperation |
| ARLID |
cav_un_auth*0296304 |
| name |
Matematicko-fyzikální fakulta KU |
| institution |
MFF KU |
| country |
CZ |
|
| confidential |
S |
| mrcbC86 |
3+4 Article Statistics Probability |
| mrcbT16-e |
STATISTICS&PROBABILITY |
| mrcbT16-f |
0.555 |
| mrcbT16-g |
0.194 |
| mrcbT16-h |
9.1 |
| mrcbT16-i |
0.00354 |
| mrcbT16-j |
0.213 |
| mrcbT16-k |
1989 |
| mrcbT16-s |
0.398 |
| mrcbT16-5 |
0.448 |
| mrcbT16-6 |
201 |
| mrcbT16-7 |
Q4 |
| mrcbT16-B |
8.453 |
| mrcbT16-C |
6.9 |
| mrcbT16-D |
Q4 |
| mrcbT16-E |
Q4 |
| mrcbT16-M |
0.37 |
| mrcbT16-N |
Q3 |
| mrcbT16-P |
6.911 |
| arlyear |
2018 |
| mrcbU14 |
85024472119 SCOPUS |
| mrcbU24 |
PUBMED |
| mrcbU34 |
000438753900017 WOS |
| mrcbU63 |
cav_un_epca*0256434 Communications in Statistics - Simulation and Computation 0361-0918 1532-4141 Roč. 47 č. 7 2018 2139 2151 Taylor & Francis |
|