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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/119852


    Title: Statistical inference based on progressively type-II censored data from the Burr X distribution under progressive-stress accelerated life test
    Authors: Mahto, A. K.;Tripathi, Y. M.;Wu, S.-J.
    Keywords: Bayes estimate;cumulative exposure model;highest posterior density interval;maximum likelihood method;Markov chain Monte Carlo;progressive censoring
    Date: 2020-09-07
    Issue Date: 2021-01-18 12:10:47 (UTC+8)
    Abstract: In this article, estimation problems for the Burr X distribution under a progressive-stress accelerated life test with progressive type-II censoring are studied. The stress is assumed to be a linearly increasing function of time. The inverse power law and the cumulative exposure model are considered. The classical and Bayesian estimations for the model parameters are obtained by using maximum likelihood method and Markov chain Monte Carlo technique,respectively. The asymptotic confidence intervals are constructed and highest posterior density intervals are also established. A simulation study is conducted to investigate the performance of the proposed point and interval estimations. Finally, a real data set is analysed for illustration.
    Relation: Journal of Statistical Computation and Simulation 91(2), p.368-382
    DOI: 10.1080/00949655.2020.1815021
    Appears in Collections:[Graduate Institute & Department of Statistics] Journal Article

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