Robust estimation of multivariate location and scatter in the presence of cellwise and casewise contamination

被引：52

作者：

Agostinelli, Claudio ^{[1
]}

Leung, Andy ^{[2
]}

Yohai, Victor J. ^{[3
]}

Zamar, Ruben H. ^{[2
]}

机构：

[1] Univ Ca Foscari Venezia, Dipartimento Sci Ambientali Informat & Stat, I-30121 Venice, Italy

[2] Univ British Columbia, Dept Stat, Vancouver, BC V6T 1Z4, Canada

[3] Univ Buenos Aires, Dept Matemat, Fac Ciencias Exactas & Nat, RA-1426 Buenos Aires, DF, Argentina

来源：

TEST | 2015年 / 24卷 / 03期

关键词：

Robust estimation; Multivariate location and scatter; Multivariate data analysis; Cellwise contamination; FAST ALGORITHM; OUTLIERS;

D O I：

10.1007/s11749-015-0450-6

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：

Multivariate location and scatter matrix estimation is a cornerstone in multivariate data analysis. We consider this problem when the data may contain independent cellwise and casewise outliers. Flat data sets with a large number of variables and a relatively small number of cases are common place in modern statistical applications. In these cases, global down-weighting of an entire case, as performed by traditional robust procedures, may lead to poor results. We highlight the need for a new generation of robust estimators that can efficiently deal with cellwise outliers and at the same time show good performance under casewise outliers.

引用

页码：441 / 461

页数：21

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