ON THE USE OF THE STEIN VARIANCE ESTIMATOR IN THE DOUBLE k-CLASS ESTIMATOR IN REGRESSION
This paper investigates the predictive mean squared error performance of a modified double k-class estimator by incorporating the Stein variance estimator. Recent studies show that the performance of the Stein rule estimator can be improved by using the Stein variance estimator. However, as we demonstrate below, this conclusion does not hold in general for all members of the double k-class estimators. On the other hand, an estimator is found to have smaller predictive mean squared error than the Stein variance-Stein rule estimator, over quite large parts of the parameter space.
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Volume (Year): 21 (2002)
Issue (Month): 1 ()
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References listed on IDEAS
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- Ullah, Aman & Ullah, Shobha, 1978. "Double k-Class Estimators of Coefficients in Linear Regression," Econometrica, Econometric Society, vol. 46(3), pages 705-22, May.
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- Gelfand, Alan E. & Dey, Dipak K., 1988. "Improved estimation of the disturbance variance in a linear regression model," Journal of Econometrics, Elsevier, vol. 39(3), pages 387-395, November.
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- Ohtani, Kazuhiro, 1988. "Optimal levels of significance of a pre-test in estimating the disturbance variance after the pre-test for a linear hypothesis on coefficients in a linear regression," Economics Letters, Elsevier, vol. 28(2), pages 151-156.
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