淡江大學機構典藏:Item 987654321/118911
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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/118911


    Title: Reliability Inference for VGA Adapter from Dual Suppliers Based on Contaminated Type-I Interval-Censored Data
    Authors: Tsai, Tzong‐Ru;Ng, Hon Keung Tony;Pham, Hoang;Lio, Yuhlong;Chiang, Jyun‐You
    Keywords: Bayesian method;location‐scale distribution;Metropolis‐Hastings algorithm;profile likelihood;Weibull distribution
    Date: 2019-06-24
    Issue Date: 2020-07-14 12:10:36 (UTC+8)
    Publisher: John Wiley & Sons Ltd.
    Abstract: Type‐I interval‐censoring scheme only documents the number of failed units within two prespecified consecutive exam times at the larger time point after putting all units on test at the initial time schedule. It is challenging to use the collected information from type‐I interval‐censoring scheme to evaluate the reliability of unit when not all admitted units are operated or tested at the same initial time and a majority of units are randomly selected to replace the failed test units at unrecorded time points. Moreover, the lifetime distribution of all pooled units from dual resources usually follows a mixture distribution. To overcome these two problems, a two‐stage inference process that consists of a data‐cleaning step and a parameter estimation step via either Markov chain Monte Carlo (MCMC) algorithm or profile likelihood method is proposed based on the contaminated type‐I interval‐censored sample from a mixture distribution with unknown proportion. An extensive simulation study is conducted under the mixture smallest extreme value distributions to evaluate the performance of the proposed method for a case study. Finally, the proposed methods are applied to the mixture lifetime distribution modeling of video graphics array adapters for the support of reliability decision.
    Relation: Quality and Reliability Engineering International 357, p.2297-2313
    DOI: 10.1002/qre.2503
    Appears in Collections:[Graduate Institute & Department of Statistics] Journal Article

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