矩阵损失下回归系数和误差方差的联合估计的可容许性的几个结果

SOME RESULTS ON ADMISSIBILITY OF SIMULTANEOUS ESTIMATES OF REGRESSION COEFFICIENTS AND ERROR VARIONCE Under Matrix Loss Function

  • 摘要: 设有线性模型:Y=(Y1,…,Yn)'=+ε=+(ε1,…,εn)',其中X:n×p已知,β=(β1,…,βp)'未知,ε1,…,εn独立,Eεi=Eεi3=0,Eε422,Fεi4=3σ4,i=1,2,…,n,0<σ2<∞,σ2未知。在矩阵损失\binomd_1-S \betad_2-\sigma^2\binomd_1-S \betad_2-\sigma^2 或 \binom\fracd_1-S \beta\sigma\fracd_2-\sigma^2\sigma^2\binom\fracd_1-S \beta\sigma\fracd_2-\sigma^2\sigma^2下,我们考虑(2)的联合估计(AY,Y'BY)在估计类\mathscrL \times \mathscrO=(CY,Y'DY):Cm×n的常数阵,D≥0为n×n的常数阵中的可容许性,得到了(AY,Y'BY)为(2)的可容许估计的一些充分条件和必要条件。

     

    Abstract: Consider linear model Y=(Y1,…,Yn)'=+ε=+(ε1,…,εn)',whereX be a n×p known design matrix, β=(β1,…,βp)', σ2>0 be unknown parameters, ε1,…,εn be independent, Eεi=Eεi3=0,Eε422,Eεi4=3σ4,i=1,2,…,n. In this parper, we give out Some necessary and Sufficient conditions for estimate(AY,Y'BY) of (, σ2) to be admissible in the class of \mathscrC \times \mathscrD=\left\\left(C Y, Y^\prime D Y\right)\right.:C be a ×n constant matrix,D be a n×n non-negative definite constant matrix under matrix \operatornameloss\binomd_1-S \betad_2-\sigma^2\binomd_1-S \betad_2-\sigma^2^\prime or \binom\fracd_1-S \beta\sigma\fracd_2-\sigma^2\sigma^2\binom\fracd_1-S \beta\sigma\fracd_2-\sigma^2\sigma^2^\prime.

     

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