Bayesian Estimation of the Limiting Availability in a Repairable One-Unit System

Q3 Mathematics
Víctor H. Salinas Torres, C. Vásquez, José S. Romeo
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引用次数: 1

Abstract

This work presents a Bayesian approach for estimating the limiting availability of an one-unit repairable system. A Bayesian analysis is developed considering an informative prior and a less informative prior distribution, respectively. Simulations are presented to study the performance of the Bayesian solutions. The maximum likelihood method is also revisited. Finally, a case study is considered, the Bayesian methodology is applied to estimate the limiting availability of a palletizer, which is used in the packaging of glass bottles. Extensions to a coherent system are also discussed.
可修单单元系统极限可用性的贝叶斯估计
本文提出了一种贝叶斯方法来估计单单元可修系统的极限可用性。贝叶斯分析分别考虑了信息先验和较少信息先验分布。通过仿真研究了贝叶斯解的性能。最大似然法也被重新审视。最后,考虑了一个案例研究,贝叶斯方法被应用于估计一个码垛机的有限可用性,这是用于包装玻璃瓶。对相干系统的扩展也进行了讨论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Revista Colombiana De Estadistica
Revista Colombiana De Estadistica STATISTICS & PROBABILITY-
CiteScore
1.20
自引率
0.00%
发文量
0
审稿时长
>12 weeks
期刊介绍: The Colombian Journal of Statistics publishes original articles of theoretical, methodological and educational kind in any branch of Statistics. Purely theoretical papers should include illustration of the techniques presented with real data or at least simulation experiments in order to verify the usefulness of the contents presented. Informative articles of high quality methodologies or statistical techniques applied in different fields of knowledge are also considered. Only articles in English language are considered for publication. The Editorial Committee assumes that the works submitted for evaluation have not been previously published and are not being given simultaneously for publication elsewhere, and will not be without prior consent of the Committee, unless, as a result of the assessment, decides not publish in the journal. It is further assumed that when the authors deliver a document for publication in the Colombian Journal of Statistics, they know the above conditions and agree with them.
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