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Title: The k-step spatial sign covariance matrix
Authors: Croux, Christophe ×
Dehon, C.
Yadine, A. #
Issue Date: Sep-2010
Publisher: Springer
Series Title: Advances in Data Analysis and Classification vol:4 issue:2-3 pages:137-150
Abstract: The Sign Covariance Matrix is an orthogonal equivariant estimator of multivariate scale. It is often used as an easy-to-compute and highly robust estimator. In this paper we propose a k-step version of the Sign Covariance Matrix, which improves its efficiency while keeping the maximal breakdown point. If k tends to infinity, Tyler’s M-estimator is obtained. It turns out that even for very low values of k, one gets almost the same efficiency as Tyler’s M-estimator.
ISSN: 1862-5347
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

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