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Stein-rule estimation under an extended balanced loss function
Abstract:This paper extends the balanced loss function to a more general setup. The ordinary least squares estimator (OLSE) and Stein-rule estimator (SRE) are exposed to this general loss function with quadratic loss structure in a linear regression model. Their risks are derived when the disturbances in the linear regression model are not necessarily normally distributed. The dominance of OLSE and SRE over each other and the effect of departure from normality assumption of disturbances on the risk property are studied.
Keywords:linear regression model  Stein-rule estimator  ordinary least squares estimator  balanced loss function  non-normal disturbances
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