Stein-rule estimation in mixed regression models

被引：1
|
作者：
Shalabh, V
Wan, ATK
机构：
[1] Panjab Univ, Dept Stat, Chandigarh 160014, India
[2] City Univ Hong Kong, Dept Management Sci, Kowloon, Hong Kong, Peoples R China
来源：
BIOMETRICAL JOURNAL | 2000年 / 42卷 / 02期
关键词：
mixed regression; risk; small disturbance; Stein-rule; Monte-Carlo experiment;
D O I：
暂无
中图分类号：
Q [生物科学];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
This paper considers a Stein-rule mixed regression estimator for estimating a normal linear regression model in the presence of stochastic linear constraints. Pie derive the small disturbance asymptotic bias and risk of the proposed estimator, and analytically compare its risk with other related estimators. A Monte-Carlo experiment investigates the empirical risk performance of the proposed estimator.
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页码：203 / 214
页数：12
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