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.
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页码：742 / 746
页数：4
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