| Article ID | Journal | Published Year | Pages | File Type | 
|---|---|---|---|---|
| 1155060 | Statistics & Probability Letters | 2009 | 8 Pages | 
Abstract
												In traditional multivariate location and scatter estimation based on the Stahel-Donoho outlyingness, a weight function is applied, usually calibrated with respect to the multivariate Gaussian distribution. Other robust methods compute the covariance matrix of a fixed size subset of the data (e.g. the MCD estimator). In this paper we study a combination of both the ideas. Location and scatter are estimated using a fixed size subset of the data containing the points with smallest Stahel-Donoho outlyingness. Local robustness and asymptotic relative efficiency are investigated.
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											Authors
												M. Debruyne, M. Hubert, 
											