聚集数据线性模型中广义岭估计相对效率问题  

Relative Efficiencies Problem of the Generalized Ridge Estimators of the Parameters in the Linear Model with Aggregated Data

作　　者：周永正[1] 孔德娟[1] 周勇[1] 

机构地区：[1]景德镇陶瓷学院,江西景德镇333403

出　　处：《南昌大学学报（工科版）》2007年第4期355-358,共4页Journal of Nanchang University(Engineering & Technology)

基　　金：景德镇市科技局科技计划资助项目(景科字[2005]18号)

摘　　要：对于聚集数据的线性模型,给出了参数的广义岭估计及改进的广义岭估计的定义,并提出了广义岭估计及改进的广义岭估计在推广的欧氏模之比意义下及加权欧氏模之比意义下的二种相对效率。分别对广义岭估计及改进的广义岭估计,得到了两种相对效率的上界。For the linear model with aggregated data, In this paper, we proposed definition of the Generalized Ridge Estimators and the Improved Generalized Ridge Estimators of the parameters and two kinds of relative effi- ciencies of the estimators, in rate of popularize Eucliden standard a sense and in rate of weighted Euclidean standard a sense. The upper bound on the two kinds of relative efficiency are obtained.

关 键 词：聚集数据 线性模型 广义岭估计 相对效率 

分 类 号：O212.1[理学—概率论与数理统计]