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The superiority of empirical Bayes estimator of parameters in linear model

Listed author(s):
  • Zhang, Weiping
  • Wei, Laisheng
  • Yang, Yaning
Registered author(s):

    In this paper, an empirical Bayes (EB) estimator is derived for the estimable functions of the parameters in normal linear model. The superiority of the EB estimator over ordinary least-squares (LS) estimator is investigated under mean square error matrix (MSEM) criterion.

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    Article provided by Elsevier in its journal Statistics & Probability Letters.

    Volume (Year): 72 (2005)
    Issue (Month): 1 (April)
    Pages: 43-50

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    Handle: RePEc:eee:stapro:v:72:y:2005:i:1:p:43-50
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    1. Laisheng Wei & Shunpu Zhang, 1995. "The convergence rates of empirical Bayes estimation in a multiple linear regression model," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 47(1), pages 81-97, January.
    2. L. Wei & G. Trenkler, 1995. "Mean square error matrix superiority of Empirical Bayes Estimators under misspecification," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 4(1), pages 187-205, June.
    3. Ghosh M. & Saleh A.K.Md.E. & Sen P.K., 1989. "Empirical Bayes Subset Estimation In Regression Models," Statistics & Risk Modeling, De Gruyter, vol. 7(1-2), pages 15-36, February.
    4. Wei, Laisheng & Chen, Jiahua, 2003. "Empirical Bayes estimation and its superiority for two-way classification model," Statistics & Probability Letters, Elsevier, vol. 63(2), pages 165-175, June.
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