期刊
STATISTICS AND COMPUTING
卷 19, 期 3, 页码 341-353出版社
SPRINGER
DOI: 10.1007/s11222-008-9096-5
关键词
Minimum covariance determinant estimator; Robust distances; Multiple outliers; Simultaneous testing; Calibration factor; Simulation
资金
- Ministero dell'Universita e della Ricerca-PRIN [2006]
Multivariate outlier detection requires computation of robust distances to be compared with appropriate cut-off points. In this paper we propose a new calibration method for obtaining reliable cut-off points of distances derived from the MCD estimator of scatter. These cut-off points are based on a more accurate estimate of the extreme tail of the distribution of robust distances. We show that our procedure gives reliable tests of outlyingness in almost all situations of practical interest, provided that the sample size is not much smaller than 50. Therefore, it is a considerable improvement over all the available MCD procedures, which are unable to provide good control over the size of multiple outlier tests for the data structures considered in this paper.
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