Admissibility in general Gauss-Markov model with respect to an ellipsoidal constraint under weighted balanced loss
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS(2022)
摘要
Under weighted balanced loss function, we obtain the best linear unbiased estimator of regression coefficient in general Gauss-Markov model and discuss the admissibility of linear estimators of the regression coefficient with respect to an ellipsoidal constraint. We establish necessary and sufficient conditions for the admissibility of the linear estimators () among the class of homogeneous and inhomogeneous linear estimators, respectively.
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关键词
Gauss-Markov model, weighted balanced loss, best linear unbiased estimator, ellipsoidal constraint, admissibility
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