On the Loss Robustness of Least-Square Estimators

被引:0
|
作者
Ghosh, Tamal [1 ]
Ghosh, Malay [1 ]
Kubokawa, Tatsuya [2 ]
机构
[1] Univ Florida, Dept Stat, 700 SW 16th Ave,209, Gainesville, FL 32601 USA
[2] Univ Tokyo, Grad Sch Econ, Tokyo, Japan
来源
AMERICAN STATISTICIAN | 2020年 / 74卷 / 01期
关键词
Divergence; Gauss-Markov theorem; Linear Risk minimization; Unbiased estimators;
D O I
10.1080/00031305.2018.1529626
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
The article revisits univariate and multivariate linear regression models. It is shown that least-square estimators (LSEs) are minimum risk estimators in general class of linear unbiased estimators under some general divergence loss. This amounts to the loss robustness of LSEs.
引用
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页码:64 / 67
页数:4
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