General Admissibility for Linear Estimators of Multivariate Random Regression Coefficients and Parameters with Respect to a Restricted Parameter Set

作     者：肖爱玲 王志忠 XIAO Ai-ling1,2,WANG Zhi-zhong(1.School of Info-physics and Geometics Engineering,Central South University,Changsha 410083,China;2.School of Informeties,Guangdong University of Foreign Studies,Guangzhou 510006,China;3.School of Mathematica Science and Computing Technology,Central South University,Changsha 410083,China)

作者机构：School of Info-physics and Geometics EngineeringCentral South University School of InformetiesGuangdong University of Foreign Studies School of Mathematica Science and Computing TechnologyCentral South University 

出 版 物：《Journal of Shanghai Jiaotong university(Science)》 (上海交通大学学报（英文版）)

年 卷 期：2009年第14卷第6期

页      面：742-746页

核心收录：

学科分类：02[经济学] 0202[经济学-应用经济学] 020208[经济学-统计学] 07[理学] 070104[理学-应用数学] 0714[理学-统计学（可授理学、经济学学位）] 070103[理学-概率论与数理统计] 0701[理学-数学] 

基　　金：the National Natural Science Foundation of China (No. 40574003) 

主　　题：parametric matrix linear estimator general optimality general admissibility 

摘      要：This paper considers the linear model effected by random disturbance,Y=XB+ε,where [~B_ε]～([^(AΘ)_0],VΣ),and ΘTATX TN XAΘΣ.It gives a definition for general admissible estimator of a linear function SΘ + GB of random regression coefficients and *** necessary and sufficient conditions for LY and LY + C to be general admissible estimators of SΘ + GB in the class of both homogenous and non-homogenous linear estimators are *** conclusion is not dependent of whether or not SΘ + GB is estimable.