Identification of Multivariate Outliers: A Performance Study

被引：0

作者：

Filzmoser, Peter ^{[1
]}

机构：

[1] Vienna Univ Technol, Dept Stat & Probabil Theory, Wiedner Hauptstr 8-10, A-1040 Vienna, Austria

来源：

AUSTRIAN JOURNAL OF STATISTICS | 2005年 / 34卷 / 02期

关键词：

Outlier Detection; MCD Estimator; Mahalanobis Distance; Robustness;

D O I：

暂无

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

Three methods for the identification of multivariate outliers (Rouss-eeuw and Van Zomeren, 1990; Becker and Gather, 1999; Filzmoser et al., 2005) are compared. They are based on the Mahalanobis distance that will be made resistant against outliers and model deviations by robust estimation of location and covariance. The comparison is made by means of a simulation study. Not only the case of multivariate normally distributed data, but also heavy tailed and asymmetric distributions will be considered. The simulations are focused on low dimensional (p = 5) and high dimensional (p = 30) data.

引用

页码：127 / 138

页数：12

共 21 条

[1]

Barnett V., 1994, OUTLIERS STAT DATA

[2]

Becker C, 1999, J AM STAT ASSOC, V94, P947

[3] The largest nonidentifiable outlier: a comparison of multivariate simultaneous outlier identification rules [J].