Robust estimation in the errors variables model via weighted likelihood estimating equations

被引：2

作者：

Basu, A ^{[1
]}

Sarkar, S ^{[1
]}

机构：

[1] OKLAHOMA STATE UNIV,DEPT STAT,STILLWATER,OK 74078

来源：

TEST | 1997年 / 6卷 / 01期

关键词：

measurement error model; disparity; Hellinger distance; robustness; weighted likelihood estimator;

D O I：

10.1007/BF02564433

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：

Parameters estimates for the errors-in-variables model are obtained by solving weighted likelihood estimating equations. They are consistent, asymptotically normal and asymptotically fully efficient, and exhibit robustness properties similar to the minimum disparity estimators (Basu and Sarkar 1994a) but are immensely simpler to compute and have some theoretical advantages over the latter. We illustrate the robustness properties through some numerical studies similar to those of Zamar (1989).

引用

页码：187 / 203

页数：17

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