Empirical Bayes Estimation of Variance Components in Two-Way Classification Random Effects Model

doi:10.7523/j.issn.2095-6134.2005.5.003

›› 2005, Vol. 22 ›› Issue (5): 545-553.DOI: 10.7523/j.issn.2095-6134.2005.5.003

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Empirical Bayes Estimation of Variance Components in Two-Way Classification Random Effects Model

WANG Li-Chun, WEI Lai-Sheng

Department of Statistics and Finance, University of Science and Technology of China, Hefei 230026, China

Received:2004-06-07 Revised:2004-11-23 Online:2005-09-15
Supported by:
supported by NSFC(19971085), the Doct oral Program Foundation of the Institute of High Education and the Special Foundation of Chinese Academy of Sciences

Abstract

Abstract:

Under weighted squared-error loss function, Bayes estimators of variance components are derived and empirical Bayes (EB) estimators are constructed by nonparametric method for balanced twoway classification random effects model. The convergence rates of EB estimators are established under suitable conditions. Finally, an example concerning the main result is given.

Key words: random effects model, variance components, Bayes estimators, empirical Bayes est imators, convergence rates

CLC Number:

O212.1

WANG Li-Chun, WEI Lai-Sheng. Empirical Bayes Estimation of Variance Components in Two-Way Classification Random Effects Model[J]. , 2005, 22(5): 545-553.

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Empirical Bayes Estimation of Variance Components in Two-Way Classification Random Effects Model

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