MSE performance of the weighted average estimators consisting of shrinkage estimators

Akio Namba and Kazuhiro Ohtani

Communications in Statistics - Theory and Methods, 2018, vol. 47, issue 5, 1204-1214

Abstract: In this paper, we consider a regression model and propose estimators which are the weighted averages of two estimators among three estimators; the Stein-rule (SR), the minimum mean squared error (MMSE), and the adjusted minimum mean-squared error (AMMSE) estimators. It is shown that one of the proposed estimators has smaller mean-squared error (MSE) than the positive-part Stein-rule (PSR) estimator over a moderate region of parameter space when the number of the regression coefficients is small (i.e., 3), and its MSE performance is comparable to the PSR estimator even when the number of the regression coefficients is not so small.

Date: 2018
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Working Paper: MSE Performance of the Weighted Average Estimators Consisting of Shrinkage Estimators (2015)
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DOI: 10.1080/03610926.2017.1316860

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