Admissibility of linear estimators of the common mean parameter in general linear models under a balanced loss function

Ming-Xiang Cao and Dao-Jiang He

Journal of Multivariate Analysis, 2017, vol. 153, issue C, 246-254

Abstract: In order to investigate linearly admissible estimators of the common mean parameter in general linear models, we introduce and motivate the use of a balanced loss function obtained by combining Zellner’s idea of balanced loss (Zellner, 1994) with the unified theory of least squares (Rao, 1973). In classes of homogeneous and non-homogeneous linear estimators, sufficient and necessary conditions for linear estimators of the common mean parameter to be admissible are obtained, respectively. A comparison is then made between linearly admissible estimators and a “truly” unified least square estimator.

Keywords: Admissibility; Balanced loss function; Linear estimators; Common mean parameter (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (2)

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DOI: 10.1016/j.jmva.2016.10.003

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