The K-Step Spatial Sign Covariance Matrix

C. Croux, C. Dehon, A. Yadine

    Research output: Working paperDiscussion paperOther research output

    14 Citations (Scopus)
    360 Downloads (Pure)


    The Sign Covariance Matrix is an orthogonal equivariant estimator of mul- tivariate 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 e±ciency 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 e±ciency as Tyler's M-estimator.
    Original languageEnglish
    Place of PublicationTilburg
    Number of pages13
    Publication statusPublished - 2010

    Publication series

    NameCentER Discussion Paper


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