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On equivalence of predictors/estimators under a multivariate general linear model with augmentation

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Assume that a true multivariate general linear model for an observed random matrix is over-parameterized by adding some new regressors due to model uncertainty. Then predictors and estimators of parameter… Click to show full abstract

Assume that a true multivariate general linear model for an observed random matrix is over-parameterized by adding some new regressors due to model uncertainty. Then predictors and estimators of parameter spaces in the true and over-parameterized models are not necessarily the same. In this article, we study the comparison problem of predictors/estimators of parameter spaces under the two models. In particular, we derive necessary and sufficient conditions for the best linear unbiased predictors/best linear unbiased estimators of the parameter spaces to be equivalent under the two models.

Keywords: linear model; general linear; multivariate general; predictors estimators; estimators parameter

Journal Title: Journal of The Korean Statistical Society
Year Published: 2017

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