\(\Phi\) admissibility of linear estimators of common mean parameter in general multivariate linear models under a balanced loss function. (English) Zbl 07531798
Summary: The definitions of \(\Phi\) optimality and \(\Phi\) 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 \(\Phi\) admissibility of linear estimators on matrix common mean parameter. Sufficient and necessary conditions for linear estimators to be \(\Phi\) admissible are obtained in classes of homogeneous and non homogeneous linear estimators, respectively.
MSC:
| 62C15 | Admissibility in statistical decision theory |
| 62J12 | Generalized linear models (logistic models) |
| 62-XX | Statistics |
Keywords:
multivariate linear models; matrix common mean parameter; balanced loss function; linear estimators; \(\Phi\) admissibilityReferences:
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