Title: Multivariate Generalized S-estimators
Authors: Roelandt, E. ×
Van Aelst, Stefan
Croux, Christophe #
Issue Date: May-2009
Publisher: Elsevier
Series Title: Journal of Multivariate Analysis vol:100 issue:5 pages:876-887
Abstract: In this paper we introduce generalized S-estimators for the multivariate regression model. This class of estimators combines high robustness and high efficiency. They are defined by minimizing the determinant of a robust estimator of the scatter matrix of differences of residuals. In the special case of a multivariate location model, the generalized Sestimator has the important independence property, and can be used for high breakdown estimation in independent component analysis. Robustness properties of the estimators are investigated by deriving their breakdown point and the influence function. We also study the efficiency of the estimators, both asymptotically and at finite samples. To obtain inference for the regression parameters, we discuss the fast and robust bootstrap for
multivariate generalized S-estimators. The method is illustrated on a real data example.
ISSN: 0047-259X
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Research Center for Operations Research and Business Statistics (ORSTAT), Leuven
Statistics Section
× corresponding author
# (joint) last author

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