淡江大學機構典藏:Item 987654321/114965
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    題名: A dynamic system for Gompertz model
    作者: YL Lio;Tzong-Ru Tsai;Nan Jiang;N. Balakrishnan
    關鍵詞: Computational approach test;generalized likelihood ratio;log-likelihood function;parametric bootstrap likelihood ratio test;sequential order statistics
    日期: 2017-11-21
    上傳時間: 2018-09-20 12:11:42 (UTC+8)
    出版者: Taylor & Francis
    摘要: Two-parameter Gompertz distribution has been introduced as a lifetime model for reliability inference recently. In this paper, the Gompertz distribution is proposed for the baseline lifetimes of components in a composite system. In this composite system, failure of a component induces increased load on the surviving components and thus increases component hazard rate via a power-trend process. Point estimates of the composite system parameters are obtained by the method of maximum likelihood. Interval estimates of the baseline survival function are obtained by using the maximum-likelihood estimator via a bootstrap percentile method. Two parametric bootstrap procedures are proposed to test whether the hazard rate function changes with the number of failed components. Intensive simulations are carried out to evaluate the performance of the proposed estimation procedure.
    關聯: Journal of Statistical Computation and Simulation 88(4), p.752-768
    DOI: 10.1080/00949655.2017.1405418
    顯示於類別:[統計學系暨研究所] 期刊論文

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