Article ID Journal Published Year Pages File Type
1146227 Journal of Multivariate Analysis 2013 13 Pages PDF
Abstract

We consider a general mixed linear model ℳℳ without any rank assumptions to the covariance matrix and without any restrictions on the correlation between the random effects vector and the random errors vector. We get the representations of best linear unbiased estimators (BLUEs)/ best linear unbiased predictors (BLUPs) of ℳℳ through a particular construction from the model ℳℳ which uses stochastic restriction. For the general mixed linear models ℳ1ℳ1 and ℳ2ℳ2, which have different covariance matrices, we derive the necessary and sufficient conditions for that the BLUEs and/or BLUPs under ℳ1ℳ1 continue to be the BLUEs and/or BLUPs under the ℳ2ℳ2. And we also give the necessary and sufficient conditions for the equivalence of BLUP under ℳ1ℳ1 and ℳ2ℳ2.

Related Topics
Physical Sciences and Engineering Mathematics Numerical Analysis
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