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 

机构地区：[1]School of Info-physics and Geometics Engineering,Central South University [2]School of Informeties,Guangdong University of Foreign Studies [3]School of Mathematica Science and Computing Technology,Central South University

出　　处：《Journal of Shanghai Jiaotong university(Science)》2009年第6期742-746,共5页上海交通大学学报（英文版）

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

摘　　要：This paper considers the linear model effected by random disturbance,Y=XB+ε,where [~B_ε]～([^(AΘ)_0],VΣ),and ΘTATX TN XAΘΣ.It gives a definition for general admissible estimator of a linear function SΘ + GB of random regression coefficients and parameters.The 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 obtained.The conclusion is not dependent of whether or not SΘ + GB is estimable.This paper considers the linear model effected by random disturbance,Y=XB＋ε,where [B_ε]-（[AΘ_0],VΣ）,and ΘTATX TN XAΘ Σ.It gives a definition for general admissible estimator of a linear function SΘ ＋ GB of random regression coefficients and parameters.The 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 obtained.The conclusion is not dependent of whether or not SΘ ＋ GB is estimable.

关 键 词：parametric matrix linear estimator general optimality general admissibility 

分 类 号：O212.1[理学—概率论与数理统计] O153.3[理学—数学]