淡江大學機構典藏:Item 987654321/58763
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    题名: On Progressive Hybrid Censored Exponential Distribution
    作者: Lin, Chien-tai;Huang, Yen-lung
    贡献者: 淡江大學數學學系
    关键词: Bayes risk;maximum-likelihood estimation;progressive hybrid censoring;simulated annealing optimization;variable sampling plan
    日期: 2012-05-01
    上传时间: 2011-10-01 21:09:24 (UTC+8)
    出版者: Taylor & Francis Ltd.
    摘要: In this paper, we introduce a new adaptive Type-I progressive hybrid censoring scheme, which has some advantages over the progressive hybrid censoring schemes already discussed in the literature. Based on an adaptive Type-I progressively hybrid censored sample, we derive the exact distribution of the maximum-likelihood estimator (MLE) of the mean lifetime of an exponential distribution as well as confidence intervals for the failure rate using exact distribution, asymptotic distribution, and three parametric bootstrap resampling methods. Furthermore, we provide computational formula for the expected number of failures and investigate the performance of the point and interval estimation for the failure rate in this case. An alternative simple form for the distribution of the MLE under adaptive Type-II progressive hybrid censoring scheme proposed by Ng et al. [Statistical analysis of exponential lifetimes under an adaptive Type-II progressive censoring scheme, Naval Res. Logist. 56 (2009), pp. 687–698] is obtained. Finally, from the exact distribution of the MLE, we establish the explicit expression for the Bayes risk of a sampling plan under adaptive Type-II progressive hybrid censoring scheme when a general loss function is used, and present some optimal Bayes solutions under four different progressive hybrid censoring schemes to illustrate the effectiveness of the proposed method.
    關聯: Journal of Statistical Computation and Simulation 82(5), pp.689-709
    DOI: 10.1080/00949655.2010.550581
    显示于类别:[數學學系暨研究所] 期刊論文

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