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    jsp.display-item.identifier=請使用永久網址來引用或連結此文件: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/20717

    题名: Bayesian inference for Rayleigh distribution under progressive censored sample
    作者: Wu, Shuo-jye;Chen, Dar-hsin;Chen, Shyi-tien
    贡献者: 淡江大學統計學系
    关键词: highest posterior density interval;predictive density;prediction interval;progressively type II censored sample;reliability function
    日期: 2006-05-01
    上传时间: 2009-11-30 12:57:35 (UTC+8)
    出版者: Wiley-Blackwell
    摘要: It is often the case that some information is available on the parameter of failure time distributions from previous experiments or analyses of failure time data. The Bayesian approach provides the methodology for incorporation of previous information with the current data. In this paper, given a progressively type II censored sample from a Rayleigh distribution, Bayesian estimators and credible intervals are obtained for the parameter and reliability function. We also derive the Bayes predictive estimator and highest posterior density prediction interval for future observations. Two numerical examples are presented for illustration and some simulation study and comparisons are performed.
    關聯: Applied Stochastic Models in Business and Industry 22(3), pp.269-279
    DOI: 10.1002/asmb.615
    显示于类别:[統計學系暨研究所] 期刊論文


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