Abstract
In this paper, we consider a linear regression model and examine the MSE performance of a heterogeneous pre-test estimator whose components are the adjusted minimum mean-squared error (AMMSE) estimator and the Stein-rule (SR) estimator. It is shown that the heterogeneous pre-test estimator dominates the SR estimator if a critical value of the pre-test is chosen appropriately. By numerical evaluations it is shown that if the number of independent variables (say, k) is 3 and the critical value of the pre-test is chosen appropriately, then the heterogeneous pre-test estimator dominates the positive-part Stein-rule (PSR) estimator. Also, when k = 4 and 5, the MSE performances of the heterogeneous pre-test and PSR estimators are comparable.
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