On sum decompositions of weighted least-squares estimators for the partitioned linear model

被引:19
|
作者
Tian, Yongge [1 ]
Takane, Yoshio [2 ]
机构
[1] Shanghai Univ Finance & Econ, Sch Econ, Shanghai 200433, Peoples R China
[2] McGill Univ, Dept Psychol, Montreal, PQ, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
matrix rank method; Moore-Penrose inverse; partitioned linear model; projector; small models; sum decompositions; WLSE;
D O I
10.1080/03610920701648862
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
For the partitioned linear model M={y, X-1 beta(1)+X-2 beta(2),sigma(2)Sigma}, this article investigates decompositions of weighted least-squares estimator (WLSE) of X-1 beta(1)+X-2 beta(2) under M as sums of WLSEs under the two small models {y, X-1 beta(1),sigma(2)Sigma} and {y, X-2 beta(2),sigma(2)Sigma}. Some consequences on the sum decomposition of the unique best unbiased linear estimator (BLUE) of X-1 beta(1)+X-2 beta(2) under M are also given.
引用
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页码:55 / 69
页数:15
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