A comparison between two competing fixed parameter constrained general linear models with new regressors. Issue 4 (4th July 2018) - Lu, Changli; Sun, Yuqin; Tian, Yongge
ABSTRACT: Assume that two competing general linear models with fixed coefficients and identical parameter restrictions are given by adding new or deleting existing unknown parameters. In this situation, estimators of the parametric functions in the contexts of the two competing models are not necessarily the same. We consider the relationships between the best linear unbiased estimators (BLUEs) of parametric functions under these two competing constricted general linear models, and derive necessary and sufficient conditions for their BLUEs to be equal.