The K-Step Spatial Sign Covariance Matrix

C. Croux, C. Dehon, A. Yadine

    Research output: Working paperDiscussion paperOther research output

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    Abstract

    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
    PublisherEconometrics
    Number of pages13
    Volume2010-41
    Publication statusPublished - 2010

    Publication series

    NameCentER Discussion Paper
    Volume2010-41

    Fingerprint

    M-estimator
    Covariance matrix
    Maximal Points
    Equivariant Estimator
    Breakdown Point
    Robust Estimators
    Infinity
    Tend

    Cite this

    Croux, C., Dehon, C., & Yadine, A. (2010). The K-Step Spatial Sign Covariance Matrix. (CentER Discussion Paper; Vol. 2010-41). Tilburg: Econometrics.
    Croux, C. ; Dehon, C. ; Yadine, A. / The K-Step Spatial Sign Covariance Matrix. Tilburg : Econometrics, 2010. (CentER Discussion Paper).
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    abstract = "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.",
    author = "C. Croux and C. Dehon and A. Yadine",
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    year = "2010",
    language = "English",
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    Croux, C, Dehon, C & Yadine, A 2010 'The K-Step Spatial Sign Covariance Matrix' CentER Discussion Paper, vol. 2010-41, Econometrics, Tilburg.

    The K-Step Spatial Sign Covariance Matrix. / Croux, C.; Dehon, C.; Yadine, A.

    Tilburg : Econometrics, 2010. (CentER Discussion Paper; Vol. 2010-41).

    Research output: Working paperDiscussion paperOther research output

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    AU - Yadine, A.

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    N2 - 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.

    AB - 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.

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    T3 - CentER Discussion Paper

    BT - The K-Step Spatial Sign Covariance Matrix

    PB - Econometrics

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    Croux C, Dehon C, Yadine A. The K-Step Spatial Sign Covariance Matrix. Tilburg: Econometrics. 2010. (CentER Discussion Paper).