The Admissibility of Linear Estimators of the Regression Coefficients under Balanced Loss Function
Haiyan Liu
Abstract
Haiyan Liu
Abstract
For a given multivariate normal linear model,a new generalized balanced loss function is defined by modifying the balanced loss function given by Zellner.The admissibility of linear estimators of the regression coefficients matrix of the multivariate normal linear model in the class of all estimators under this loss has been studied,the necessary and sufficient condition is given.This method can also be used in the study of the admissibility of linear estimators in the class of all linear estimators and other definitions of admissibility.
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For a given multivariate normal linear model,a new generalized balanced loss function is defined by modifying the balanced loss function given by Zellner.The admissibility of linear estimators of the regression coefficients matrix of the multivariate normal linear model in the class of all estimators under this loss has been studied,the necessary and sufficient condition is given.This method can also be used in the study of the admissibility of linear estimators in the class of all linear estimators and other definitions of admissibility.
Key concepts: Estimator, Linear regression, Mathematics, Linear model, Linear predictor function, Bayesian multivariate linear regression, Multivariate statistics, Function (biology)