The multivariate least-trimmed squares estimator

被引：82

作者：

Agullo, Jose ^{[3
]}

Croux, Christophe ^{[2
]}

Van Aelst, Stefan ^{[1
]}

机构：

[1] Ghent Univ UGENT, Dept Appl Math & Comp Sci, B-9000 Ghent, Belgium

[2] Katholieke Univ Leuven, ORSTAT Res Ctr, Fac Econ & Appl Econ, B-3000 Louvain, Belgium

[3] Univ Alicante, Dept Fundamentos Anal Econ, E-03080 Alicante, Spain

来源：

JOURNAL OF MULTIVARIATE ANALYSIS | 2008年 / 99卷 / 03期

关键词：

multivariate regression; breakdown point; influence function; minimum covariance determinant estimator;

D O I：

10.1016/j.jmva.2006.06.005

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：

In this paper we introduce the least-trimmed squares estimator for multivariate regression. We give three equivalent formulations of the estimator and obtain its breakdown point. A fast algorithm for its computation is proposed. We prove Fisher-consistency at the multivariate regression model with elliptically symmetric error distribution and derive the influence function. Simulations investigate the finite-sample efficiency and robustness of the estimator. To increase the efficiency of the estimator, we also consider a one-step reweighted estimator. (C) 2006 Elsevier Inc. All rights reserved.

引用

页码：311 / 338

页数：28

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