淡江大學機構典藏:Item 987654321/113396
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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/113396


    Title: Reliability inference based on the three-parameter Burr type XII distribution with type II censoring
    Authors: Hua Xin;Jianping Zhu;Junge Sun;Chenlu Zheng;Tzong-Ru Tsai
    Keywords: Gamma distribution;Gibbs sampling;important sampling;Markov chain Monte Carlo;maximum likelihood estimation
    Date: 2018-01-19
    Issue Date: 2018-05-10 12:10:50 (UTC+8)
    Abstract: The three-parameter Burr type XII distribution (3pBXIID) is quite flexible and contains a wide range of distribution shapes for fitting lifetime data. However, it is difficult to obtain reliable estimates of the 3pBXIID quantiles from censored samples for evaluating the reliability of lifetime data. In this work, a Metropolis–Hastings Markov chain Monte Carlo (M-H MCMC) procedure is proposed to obtain reliable maximum likelihood estimates (MLEs) of the 3pBXIID quantiles from a type II censored sample. Moreover, the parametric bootstrap percentile procedure is used to obtain the confidence interval of the quantile of the 3pBXIID. The performance of the proposed M-H MCMC method is evaluated in view of Monte Carlo simulations. Two examples, regarding the survival lifetimes of breast cancer patients and the reliability inference on the lifetimes of oil-well pumps for sucker-rod oil pumping systems, are applied to illustrate the applications of the proposed M-H MCMC method and bootstrap procedure.
    Relation: International Journal of Reliability, Quality and Safety Engineering 25(2), p.1850010
    DOI: 10.1142/S0218539318500109
    Appears in Collections:[Graduate Institute & Department of Statistics] Journal Article

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