Stein-rule estimation under an extended balanced loss function

作     者：Shalabh Toutenburg, H. Heumann, C. 

作者机构：Indian Inst Technol Dept Math & Stat Kanpur 208016 Uttar Pradesh India Univ Munich Dept Stat Munich Germany 

出 版 物：《JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION》 (统计计算与模拟杂志)

年 卷 期：2009年第79卷第10期

页      面：1259-1273页

核心收录：

学科分类：0202[经济学-应用经济学] 02[经济学] 020208[经济学-统计学] 07[理学] 0714[理学-统计学（可授理学、经济学学位）] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Alexander von Humboldt Foundation  Germany 

主　　题：linear regression model Stein-rule estimator ordinary least squares estimator balanced loss function non-normal disturbances 

摘      要：This paper extends the balanced loss function to a more general setup. The ordinary least squares estimator (OLSE) and Stein-rule estimator (SRE) are exposed to this general loss function with quadratic loss structure in a linear regression model. Their risks are derived when the disturbances in the linear regression model are not necessarily normally distributed. The dominance of OLSE and SRE over each other and the effect of departure from normality assumption of disturbances on the risk property are studied.