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    题名: Testing in two parameter exponential distributions via empirical Bayes method
    作者: 黃文濤;Huang, Wen-tao;Shih, Ching-jui
    贡献者: 淡江大學經營決策學系
    关键词: Asymptotically optimal;Empirical Bayes;Rate of convergence;Regret
    日期: 2009-05
    上传时间: 2010-08-09 17:01:29 (UTC+8)
    出版者: Springer
    摘要: A monotone empirical Bayes test δ n * for testing the hypotheses H 0:θ≤θ 0 versus H 1:θ>θ 0 using a linear error loss in the two-parameter exponential distribution having probability density , x>θ>0, with unknown scale parameter β is considered. The asymptotic optimality of δ n * is studied and under certain regularity conditions, it is shown that the regret of δ n * converges to zero at a rate , where n is the number of past data available and r is some related positive integer with 0≤α≤1. The rate improves significantly the result of [10] under unknown β.
    關聯: Journal of Applied Mathematics and Computing 30(1-2), pp.409-426
    DOI: 10.1007/s12190-008-0181-x
    显示于类别:[管理科學學系暨研究所] 期刊論文


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