Publication
Title
Robust factor analysis
Author
Abstract
Our aim is to construct a factor analysis method that can resist the effect of outliers. For this we start with a highly robust initial covariance estimator, after which the factors can be obtained from maximum likelihood or from principal factor analysis (PFA). We find that PFA based on the minimum covariance determinant scatter matrix works well. We also derive the influence function of the PFA method based on either the classical scatter matrix or a robust matrix. These results are applied to the construction of a new type of empirical influence function (EIF), which is very effective for detecting influential data. To facilitate the interpretation, we compute a cutoff value for this EIF. Our findings are illustrated with several real data examples. (C) 2003 Elsevier Science (USA). All rights reserved.
Language
English
Source (journal)
Journal of multivariate analysis. - New York, N.Y.
Publication
New York, N.Y. : 2003
ISSN
0047-259X
DOI
10.1016/S0047-259X(02)00007-6
Volume/pages
84 :1 (2003) , p. 145-172
ISI
000181352700008
Full text (Publisher's DOI)
Full text (open access)
UAntwerpen
Faculty/Department
Research group
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Web of Science
Record
Identifier
Creation 03.01.2013
Last edited 23.08.2022
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