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http://hdl.handle.net/1942/8004
Title: | MSE superiority of Bayes and empirical Bayes estimators in two generalized seemingly unrelated regressions | Authors: | WANG, Lichun VERAVERBEKE, Noel |
Issue Date: | 2008 | Publisher: | ELSEVIER SCIENCE BV | Source: | STATISTICS & PROBABILITY LETTERS, 78(2). p. 109-117 | Abstract: | This paper deals with the estimation problem in a system of two seemingly unrelated regression equations where the regression parameter is distributed according to the normal prior distribution N(beta(0), sigma(2)(beta)Sigma(beta)). Resorting to the covariance adjustment technique, we obtain the best Bayes estimator of the regression parameter and prove its superiority over the best linear unbiased estimator (BLUE) in terms of the mean square error (MSE) criterion. Also, under the MSE criterion, we show that the empirical Bayes estimator of the regression parameter is better than the Zellner type estimator when the covariance matrix of error variables is unknown. (c) 2007 Elsevier B.V. All rights reserved. | Notes: | Jiao Tong Univ, Dept Math, Beijing 100044, Peoples R China. Hasselt Univ, Ctr Stat, B-3590 Diepenbeek, Belgium.Wang, L, Jiao Tong Univ, Dept Math, Beijing 100044, Peoples R China.wlc@amss.ac.cn | Keywords: | Bayes method; seemingly unrelated regressions; covariance adjusted approach; mean square error criterion | Document URI: | http://hdl.handle.net/1942/8004 | Link to publication/dataset: | http/dx.doi.org/10.1016/j.spl.2007.05.008 | ISSN: | 0167-7152 | e-ISSN: | 1879-2103 | ISI #: | 000252908500002 | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2009 |
Appears in Collections: | Research publications |
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MSE Superiority of Bayes and Empirical.pdf | Peer-reviewed author version | 134.77 kB | Adobe PDF | View/Open |
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