Robust weighted orthogonal regression in the errors-in-variables model

被引:32
作者
Fekri, M
Ruiz-Gazen, A
机构
[1] Univ Toulouse 1, UMR CNRS C5604, GREMAQ, F-31000 Toulouse, France
[2] Univ Toulouse 3, UMR CNRS C5583, Lab Stat & Probabil, F-31062 Toulouse 4, France
[3] Inst Natl Postes & Telecommun, Dept Informat & Math Appl, Rabat, Morocco
关键词
errors-in-variables model; general least squares; robustness; influence function; M-estimators; S-estimators; MCD estimator;
D O I
10.1016/S0047-259X(03)00057-5
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
This paper focuses on robust estimation in the structural errors-in-variables (EV) model. A new class of robust estimators, called weighted orthogonal regression estimators, is introduced. Robust estimators of the parameters of the EV model are simply derived from robust estimators of multivariate location and scatter such as the M-estimators, the S-estimators and the MCD estimator. The influence functions of the proposed estimators are calculated and shown to be bounded. Moreover, we derive the asymptotic distributions of the estimators and illustrate the results on simulated examples and on a real-data set. (C) 2003 Elsevier Inc. All rights reserved.
引用
收藏
页码:89 / 108
页数:20
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