THE RELATIVE EFFICIENCIES OF LEAST SQUARES IN LINEAR MODELS  

作　　者：陈建宝 詹金龙 

出　　处：《Acta Mathematica Scientia》1994年第S1期103-109,共7页数学物理学报（B辑英文版）

摘　　要：The present paper daisses the relative efficiencies of the least square estimates in linear models. For Gauss-Markoff model: Y=Xe + e E(e)= 0, Cov(e)=V, an new efficiencyo f least square estimate for linearly estimable function c'r is proposed and its lower bound is giv-en. For variance component model: Y=X + e, E(e)=0, Cov(e)=, an new efficiency of least square estimate for linearly estimable function C'r is introduced for the first timeand its lower bound, which is independent of unknown parameters, is also obtained.The present paper daisses the relative efficiencies of the least square estimates in linear models. For Gauss-Markoff model: Y=Xe + e E(e)= 0, Cov(e)=V, an new efficiencyo f least square estimate for linearly estimable function c'r is proposed and its lower bound is giv-en. For variance component model: Y=X + e, E(e)=0, Cov(e)=, an new efficiency of least square estimate for linearly estimable function C'r is introduced for the first timeand its lower bound, which is independent of unknown parameters, is also obtained.

关 键 词：Linear model Gauss-Markov. Variance component LSE BLUE Efficiency. 

分 类 号：O21[理学—概率论与数理统计]