Publication
Title
Small sample corrections for LTS and MCD
Author
Abstract
The least trimmed squares estimator and the minimum covariance determinant estimator [6] are frequently used robust estimators of regression and of location and scatter, Consistency factors can be computed for both methods to make the estimators consistent at the normal model. However, for small data sets these factors do not make the estimator unbiased. Based on simulation studies we therefore construct formulas which allow us to compute small sample correction factors for all sample sizes and dimensions without having to carry out any new simulations. We give some examples to illustrate the effect of the correction factor.
Language
English
Source (journal)
Metrika : Zeitschrift für theoretische und angewandte Statistik. - Heidelberg, 1958, currens
Source (book)
International Conference on Robust Statistics, JUL 23-27, 2001, VORAU, AUSTRIA
Publication
Heidelberg : 2002
ISSN
0026-1335 [print]
1435-926X [online]
DOI
10.1007/S001840200191
Volume/pages
55 :1-2 (2002) , p. 111-123
ISI
000175702200011
Full text (Publisher's DOI)
Full text (publisher's version - intranet only)
UAntwerpen
Faculty/Department
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Web of Science
Record
Identifier
Creation 03.01.2013
Last edited 04.03.2024
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