The minimum weighted covariance determinant estimator revisited
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F22%3A00522579" target="_blank" >RIV/67985807:_____/22:00522579 - isvavai.cz</a>
Alternative codes found
RIV/00216208:11320/22:10472362
Result on the web
<a href="https://dx.doi.org/10.1080/03610918.2020.1725818" target="_blank" >https://dx.doi.org/10.1080/03610918.2020.1725818</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1080/03610918.2020.1725818" target="_blank" >10.1080/03610918.2020.1725818</a>
Alternative languages
Result language
angličtina
Original language name
The minimum weighted covariance determinant estimator revisited
Original language description
This paper is devoted to robust estimation of parameters of multivariate data. It investigates the minimum weighted covariance determinant estimator, which is based on implicit weights assigned to individual observations and is highly resistant to the presence of outlying values (outliers). We propose alternative versions of the estimator, which can be computed by means of the same (approximate) algorithm. Based on numerical experiments, we recommend especially a version of the estimator based on minimizing the product of (only) several eigenvalues of the weighted covariance matrix of the data. This version is namely able to overcome the performance of several available estimators including MM-estimators on contaminated data. Another proposal with promising performance is a two-stage adaptive weighting scheme for the estimator.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
10103 - Statistics and probability
Result continuities
Project
<a href="/en/project/GA18-01137S" target="_blank" >GA18-01137S: Random Processes of Regression Quantiles in the Financial Risk Analysis</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Communications in Statistics - Simulation and Computation
ISSN
0361-0918
e-ISSN
1532-4141
Volume of the periodical
51
Issue of the periodical within the volume
7
Country of publishing house
US - UNITED STATES
Number of pages
13
Pages from-to
3888-3900
UT code for WoS article
000513415700001
EID of the result in the Scopus database
2-s2.0-85079382560