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MSE performance of a heterogeneous pre-test estimator

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Author Info
Ohtani, Kazuhiro

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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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File URL: http://www.sciencedirect.com/science/article/B6V1D-3VMW8P8-S/2/d41cba278a3c84aa781b822d916d5d38
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Publisher Info
Article provided by Elsevier in its journal Statistics & Probability Letters.

Volume (Year): 41 (1999)
Issue (Month): 1 (January)
Pages: 65-71
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Handle: RePEc:eee:stapro:v:41:y:1999:i:1:p:65-71

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Related research
Keywords: Adjusted minimum MSE estimator MSE Positive-part Stein-rule estimator Heterogeneous pre-test estimator Stein-rule estimator;

Cited by:
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  1. Alan Wan & Anoop Chaturvedi, 2000. "Operational Variants of the Minimum Mean Squared Error Estimator in Linear Regression Models with Non-Spherical Disturbances," Annals of the Institute of Statistical Mathematics, Springer, vol. 52(2), pages 332-342, June. [Downloadable!] (restricted)
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