The influence function of the Stahel–Donoho covariance estimator of smallest outlyingness
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. th...
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Veröffentlicht in: | Statistics & probability letters 2009-02, Vol.79 (3), p.275-282 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | 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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ISSN: | 0167-7152 1879-2103 |
DOI: | 10.1016/j.spl.2008.08.006 |