| 3 | Bayesian Inference on Type-Ⅰ Progressively Hybrid Competing Risks Model显示文摘In this paper, we construct a Bayesian framework combining Type-Ⅰ progressively hybrid censoring scheme and competing risks which are independently distributed as exponentiated Weibull distribution with one scale parameter and two shape parameters. Since there exist unknown hyper-parameters in prior density functions of shape parameters, we consider the hierarchical priors to obtain the individual marginal posterior density functions,Bayesian estimates and highest posterior density credible intervals. As explicit expressions of estimates cannot be obtained, the componentwise updating algorithm of Metropolis-Hastings method is employed to compute the numerical results. Finally, it is concluded that Bayesian estimates have a good performance. | ZHANG Chun-fang Sill Yi-min WU Min | 2018 | Chinese Quarterly Journal of Mathematics2018，33，2： | 0 |
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