Robust estimators based on generalization of trimmed mean

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F18%3A00481224" target="_blank" >RIV/67985556:_____/18:00481224 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1080/03610918.2017.1337136" target="_blank" >http://dx.doi.org/10.1080/03610918.2017.1337136</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1080/03610918.2017.1337136" target="_blank" >10.1080/03610918.2017.1337136</a>

Result language

angličtina

Original language name

Robust estimators based on generalization of trimmed mean

Original language description

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.

Czech name

—

Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

10101 - Pure mathematics

Project

—

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2018

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Communications in Statistics - Simulation and Computation and Communications in Statistics Part B - Simulation and Computation

ISSN

0361-0918

e-ISSN

—

Volume of the periodical

47

Issue of the periodical within the volume

7

Country of publishing house

US - UNITED STATES

Number of pages

13

Pages from-to

2139-2151

UT code for WoS article

000438753900017

EID of the result in the Scopus database

2-s2.0-85024472119