Influence functions and outlier detection under the common principal components model: A robust approach

被引：26

作者：

Boente, G

Pires, AM

Rodrigues, IM

机构：

[1] Consejo Nacl Invest Cient & Tecn, Dept Matemat, RA-1428 Buenos Aires, DF, Argentina

[2] Inst Calculo, RA-1428 Buenos Aires, DF, Argentina

[3] Univ Tecn Lisboa, Dept Matemat, Inst Super Tecn, P-1049001 Lisbon, Portugal

来源：

BIOMETRIKA | 2002年 / 89卷 / 04期

关键词：

asymptotic variance; common principal components; partial influence function; projection-pursuit; robust estimation; robust scatter matrix;

D O I：

10.1093/biomet/89.4.861

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

The common principal components model for-several. groups of multivariate observations assumes equal principal axes but different variances along these axes among the groups. Influence functions for plug-in and projection-pursuit estimates under a common principal component model are obtained. Asymptotic variances are derived from them. Outlier detection is possible using partial influence functions.

引用

页码：861 / 875

页数：15

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