Title: High breakdown estimators for principal components: the projection-pursuit approach revisited
Authors: Croux, Christophe ×
Ruiz-Gazen, A #
Issue Date: Jul-2005
Publisher: Elsevier inc
Series Title: Journal of multivariate analysis vol:95 issue:1 pages:206-226
Abstract: Li and Chen (J. Amer. Statist. Assoc. 80 (1985) 759) proposed a method for principal components using projection-pursuit techniques. In classical principal components one searches for directions with maximal variance, and their approach consists of replacing this variance by a robust scale measure. Li and Chen showed that this estimator is consistent, qualitative robust and inherits the breakdown point of the robust scale estimator. We complete their study by deriving the influence function of the estimators for the eigenvectors, eigenvalues and the associated dispersion matrix. Corresponding Gaussian efficiencies are presented as well. Asymptotic normality of the estimators has been treated in a paper of Cui et al. (Biometrika 90 (2003) 953), complementing the results of this paper. Furthermore, a simple explicit version of the projection-pursuit based estimator is proposed and shown to be fast to compute, orthogonally equivariant, and having the maximal finite-sample breakdown point property. We will illustrate the method with a real data example. (c) 2004 Elsevier Inc. All rights reserved.
ISSN: 0047-259X
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Research Center for Operations Research and Business Statistics (ORSTAT), Leuven
× corresponding author
# (joint) last author

Files in This Item:
File Status SizeFormat
pppca.pdf Published 329KbAdobe PDFView/Open


All items in Lirias are protected by copyright, with all rights reserved.

© Web of science