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MSE dominance of the pre-test iterative variance estimator over the iterative variance estimator in regression

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  • Ohtani, Kazuhiro

Abstract

In this paper, we examine the small sample properties of the pre-test iterative variance estimator in regression. The explicit formula of MSE is derived, and it is shown that the pre-test iterative variance estimator with an appropriate critical value dominates the iterative variance estimator without pre-testing in terms of MSE. We also compare the MSE performances of the pre-test iterative variance estimators using the Stein-rule, minimum mean squared error, and adjusted minimum mean squared error estimators by numerical evaluations.

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  • Ohtani, Kazuhiro, 2001. "MSE dominance of the pre-test iterative variance estimator over the iterative variance estimator in regression," Statistics & Probability Letters, Elsevier, vol. 54(3), pages 331-340, October.
    • Handle: RePEc:eee:stapro:v:54:y:2001:i:3:p:331-340
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    References listed on IDEAS

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    1. Ullah, Aman & Ullah, Shobha, 1978. "Double k-Class Estimators of Coefficients in Linear Regression," Econometrica, Econometric Society, vol. 46(3), pages 705-722, May.
    2. Wan, Alan T. K. & Kurumai, Hiroko, 1999. "An iterative feasible minimum mean squared error estimator of the disturbance variance in linear regression under asymmetric loss," Statistics & Probability Letters, Elsevier, vol. 45(3), pages 253-259, November.
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