淡江大學機構典藏:Item 987654321/123293
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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/123293


    Title: Stress–strength inference on the multicomponent model based on generalized exponential distributions under type-I hybrid censoring
    Authors: Tsai, Tzong-Ru;Lio, YL;Chiang, J-Y;Chang, Y-W
    Keywords: multicomponent stress–strength model;generalized exponential distribution;Bayesian method;Markov chain Monte Carlo method;highest probability density interval
    Date: 2023-03-04
    Issue Date: 2023-04-28 17:33:34 (UTC+8)
    Publisher: MDPI AG
    Abstract: The stress–strength analysis is investigated for a multicomponent system, where all strength variables of components follow a generalized exponential distribution and are subject to the generalized exponential distributed stress. The estimation methods of the maximum likelihood and Bayesian are utilized to infer the system reliability. For the Bayesian estimation method, informative and non-informative priors combined with three loss functions are considered. Because the computational difficulty on working posteriors, the Markov chain Monte Carlo method is adopted to obtain the approximation of the reliability estimator posterior. In addition, the bootstrap method and highest probability density interval are used to obtain the reliability confidence intervals. The simulation study shows that the Bayes estimator with informative prior is superior to other competitors. Finally, two real examples are given to illustrate the proposed estimation methods.
    Relation: Mathematics 2023 11(5), 1249
    DOI: 10.3390/math11051249
    Appears in Collections:[Graduate Institute & Department of Statistics] Journal Article

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