Title of article
Some equalities for estimations of variance components in a general linear model and its restricted and transformed models
Author/Authors
Tian، نويسنده , , Yongge and Liu، نويسنده , , Chunmei، نويسنده ,
Issue Information
دوفصلنامه با شماره پیاپی سال 2010
Pages
11
From page
1959
To page
1969
Abstract
For the unknown positive parameter σ 2 in a general linear model ℳ = { y , X β , σ 2 Σ } , the two commonly used estimations are the simple estimator (SE) and the minimum norm quadratic unbiased estimator (MINQUE). In this paper, we derive necessary and sufficient conditions for the equivalence of the SEs and MINQUEs of the variance component σ 2 in the original model ℳ , the restricted model ℳ r = { y , X β ∣ A β = b , σ 2 Σ } , the transformed model ℳ t = { A y , A X β , σ 2 A Σ A ′ } , and the misspecified model ℳ m = { y , X 0 β , σ 2 Σ 0 } .
Keywords
linear regression model , Restricted model , Transformed model , Sub-sample model , reduced model , Simple estimator , Minimum norm quadratic unbiased estimator , Matrix rank method , Equality for estimators
Journal title
Journal of Multivariate Analysis
Serial Year
2010
Journal title
Journal of Multivariate Analysis
Record number
1565477
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