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EMPIRICAL BAYES TEST PROBLEMS OF VARIANCE COMPONENTS IN RANDOM EFFECTS MODEL 被引量:3

EMPIRICAL BAYES TEST PROBLEMS OF VARIANCE COMPONENTS IN RANDOM EFFECTS MODEL
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摘要 Bayes decision rule of variance components for one-way random effects model is derived and empirical Bayes (EB) decision rules are constructed by kernel estimation method. Under suitable conditions, it is shown that the proposed EB decision rules are asymptotically optimal with convergence rates near O(n-1/2). Finally, an example concerning the main result is given. Bayes decision rule of variance components for one-way random effects model is derived and empirical Bayes (EB) decision rules are constructed by kernel estimation method. Under suitable conditions, it is shown that the proposed EB decision rules are asymptotically optimal with convergence rates near O(n-1/2). Finally, an example concerning the main result is given.
出处 《Acta Mathematica Scientia》 SCIE CSCD 2005年第2期274-282,共9页 数学物理学报(B辑英文版)
基金 The project is partly supported by NSFC (19971085)the Doctoral Program Foundation of the Institute of High Education and the Special Foundation of Chinese Academy of Sciences.
关键词 Empirical Bayes test variance components random effects model convergence rates Empirical Bayes test, variance components, random effects model, convergence rates
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