一类相依回归模型参数估计的相对效率  

Relative efficiencies of parameter estimator in a class of seemingly unrelated regression model

作　　者：王志福[1] 刘春梅[1] 宓颖[1] 

机构地区：[1]渤海大学数学系,辽宁锦州121013

出　　处：《渤海大学学报（自然科学版）》2005年第3期249-252,共4页Journal of Bohai University:Natural Science Edition

摘　　要：对于一类相依回归系统(1),当设计阵X1呈病态时,文[1]中提出了协方差阵已知或未知时,估计量β~1、β1^(T)的改进估计分别为β~1(k)、β1^(T,k)。讨论这两种有偏估计与它们的协方差改进估计β1~,β~1(T)及最小二乘估计β1∧之间的相对效率问题,并给出了相对效率的上界或下界。For a chass of seemingly unrelated regression system(1),when the design matrix X_1 is ill-conditioned,Wang song-gui has proposed improvement estimators _1(k)、_1(T,k) of covariance improvement estimators _1、_1(T) for covariance matrix V is known or unknown in[1].We will discuss the relative efficiencies of the two biased estimators to their own covatiance improvement estimator _1,_1(T) and least square estimator _1,and the lower bound or upper bound is given.

关 键 词：相依回归模型 有偏估计 协方差改进估计 最小二乘估计 相对效率 

分 类 号：O212[理学—概率论与数理统计]