Φ admissibility of linear estimators of common mean parameter in general multivariate linear models under a balanced loss function
Mingxiang Cao, Junyong Park, Guangjun Shen
Abstract
Mingxiang Cao, Junyong Park, Guangjun Shen
Abstract
The definitions of Φ optimality and Φ admissibility of matrix common mean parameter are given in general multivariate linear models under a generalized matrix balanced loss function. We extend some previous studies to more general cases such that Φ admissibility of linear estimators on matrix common mean parameter. Sufficient and necessary conditions for linear estimators to be Φ admissible are obtained in classes of homogeneous and non homogeneous linear estimators, respectively.
A significance statement is not available in the OpenAlex record.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
The definitions of Φ optimality and Φ admissibility of matrix common mean parameter are given in general multivariate linear models under a generalized matrix balanced loss function. We extend some previous studies to more general cases such that Φ admissibility of linear estimators on matrix common mean parameter. Sufficient and necessary conditions for linear estimators to be Φ admissible are obtained in classes of homogeneous and non homogeneous linear estimators, respectively.
Key concepts: Estimator, Mathematics, Applied mathematics, Multivariate statistics, Matrix (chemical analysis), Linear model, Homogeneous, Function (biology)