Breakdown points of penalized and hybrid M-estimators of covariance
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We introduce a class of hybrid M-estimators of multivariate scatter which, analogous to the popular spatial sign covariance matrix (SSCM), possess high breakdown points. We also show that the SSCM can be viewed as an extreme member of this class. Unlike the SSCM, but like the regular M-estimators of scatter, this new class of estimators takes into account the shape of the contours of the data cloud for downweighting observations.
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