General admissibility for linear estimators of multivariate random regression coefficients and parameters with respect to a restricted parameter set

被引：0

作者：

Xiao A.-L. ^{[1
,2
]}

Wang Z.-Z. ^{[3
]}

机构：

[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

来源：

Journal of Shanghai Jiaotong University (Science) | 2009年 / 14卷 / 6期

关键词：

General admissibility; General optimality; Linear estimator; Parametric matrix;

D O I：

10.1007/s12204-009-0742-7

中图分类号：

学科分类号：

摘要：

This paper considers the linear model effected by random disturbance, Y=XB+ε. 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. Copyright.

引用

页码：742 / 746

页数：4