A local influence approach to identifying multiple multivariate outliers

被引:10
|
作者
Poon, WY [1 ]
Lew, SF
Poon, YS
机构
[1] Chinese Univ Hong Kong, Dept Stat, Shatin, Hong Kong, Peoples R China
[2] Univ Calif Riverside, Riverside, CA 92521 USA
来源
BRITISH JOURNAL OF MATHEMATICAL & STATISTICAL PSYCHOLOGY | 2000年 / 53卷
关键词
D O I
10.1348/000711000159321
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
We make use of Cook's local influence approach and its recent modification by Poon and Poon to develop measures for detecting multivariate outliers. The motivation and the foundation of the theory are geometrical and are different from classical approaches: however, whilst the proposed measure exhibits a form similar to those in the literature, it still has a considerable advantage in having transformed the classical measures to the unit interval. The new approach unifies outlier identification measures using geometrical concepts. It involves no distributional assumption or large-sample properties, and allows the flexibility of identifying outliers with respect to different metrics. The approach therefore provides a valid reason for using the various measures in complicated situations, such as in non-normal cases and in small-sample problems.
引用
收藏
页码:255 / 273
页数:19
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