Publication
Title
Stahel-Donoho estimators with cellwise weights
Author
Abstract
The Stahel-Donoho estimator is defined as a weighted mean and covariance, where each observation receives a weight which depends on a measure of its outlyingness. Therefore, all variables are treated in the same way whether they are responsible for the outlyingness or not. We present an adaptation of the Stahel-Donoho estimator, where we allow separate weights for each variable. By using cellwise weights, we aim to only downweight the contaminated variables such that we avoid losing the information contained in the other variables. The goal is to increase the precision and possibly the robustness, of the estimator. We compare several variants of our proposal and show to what extent they succeed in identifying and downweighting precisely those variables which are contaminated. We further demonstrate that in many situations the mean-squared error of the adapted estimators is lower than that of the original Stahel-Donoho estimator and that this results in better outlier detection capabilities. We also consider some real data examples.
Language
Dutch
Source (journal)
Journal of statistical computation and simulation. - New York, N.Y., 1972, currens
Publication
New York, N.Y. : Gordon and Breach Science Publishers, 2011
ISSN
0094-9655 [print]
1563-5163 [online]
Volume/pages
81:1(2011), p. 1-27
ISI
000285347900001
Full text (Publisher's DOI)
UAntwerpen
Faculty/Department
Research group
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Web of Science
Record
Identification
Creation 08.02.2011
Last edited 19.09.2017
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