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The minimum weighted covariance determinant estimator

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Abstract

In this paper, we introduce weighted estimators of the location and dispersion of a multivariate data set with weights based on the ranks of the Mahalanobis distances. We discuss some properties of the estimators like the breakdown point, influence function and asymptotic variance. The outlier detection capacities of different weight functions are compared. A simulation study is given to investigate the finite-sample behavior of the estimators.

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Authors and Affiliations

  1. Department of Applied Mathematics and Computer Science, Ghent University, UGent, Krijgslaan 281 S9, 9000, Gent, Belgium

    Ella Roelant, Stefan Van Aelst & Gert Willems

Authors
  1. Ella Roelant
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  2. Stefan Van Aelst
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  3. Gert Willems
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Corresponding author

Correspondence to Ella Roelant.

Additional information

The research of Stefan Van Aelst was supported by a grant of the Fund for Scientific Research-Flanders (FWO-Vlaanderen) and by IAP research network grant nr. P6/03 of the Belgian government (Belgian Science Policy).

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Roelant, E., Van Aelst, S. & Willems, G. The minimum weighted covariance determinant estimator. Metrika 70, 177–204 (2009). https://doi.org/10.1007/s00184-008-0186-3

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