期刊
ANNALS OF STATISTICS
卷 37, 期 1, 页码 311-331出版社
INST MATHEMATICAL STATISTICS
DOI: 10.1214/07-AOS588
关键词
Breakdown point; contamination model; independent contamination; influence function; robustness
资金
- Fund for Scientific Research-Flanders (FWO-Vlaanderen)
- Belgian government (Belgian Science Policy) [P6/03]
- Universidad de Buenos Aires [X-094]
- CONICET, Argentina [PIP 5505]
- ANPCyT, Argentina [PICT 21407]
- NSERC
We investigate the performance of robust estimates of multivariate location under nonstandard data contamination models such as componentwise outliers (i.e., contamination in each variable is independent from the other variables). This model brings up a possible new source of statistical error that we call propagation of outliers. This source of error is Unusual in the sense that it is generated by the data processing itself and takes place after the data has been collected. We define and derive the influence function of robust multivariate location estimates under flexible contamination models and use it to investigate the effect of propagation of outliers. Furthermore, we show that standard high-breakdown affine equivariant estimators propagate outliers and therefore show poor breakdown behavior under componentwise contamination when the dimension d is high.
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