Application of Bayesian Methods in Reliability Data Analyses Li, Ming Meeker, William Meeker, William
dc.contributor.department Statistics 2018-02-16T21:13:13.000 2020-07-02T06:56:25Z 2020-07-02T06:56:25Z 2013-05-01
dc.description.abstract <p>The development of the theory and application of Monte Carlo Markov Chain methods, vast improvements in computational capabilities and emerging software alternatives have made it possible for more frequent use of Bayesian methods in reliability applications. Bayesian methods, however, remain controversial in Reliability (and some other applications) because of the concern about where the needed prior distributions should come from. On the other hand, there are many applications where engineers have solid prior information on certain aspects of their reliability problems based on physics of failure or previous experience with the same failure mechanism. For example, engineers often have useful but imprecise knowledge about the effective activation energy in a temperature-accelerated life test or about the Weibull shape parameter in the analysis of fatigue failure data. In such applications, the use of Bayesian methods is compelling as it offers an appropriate compromise between assuming that such quantities are known and assuming that nothing is known. In this paper we compare the use of Bayesian methods with the traditional maximum likelihood methods for a group of examples including the analysis of field data with multiple censoring, accelerated life test data, and accelerated degradation test data.</p>
dc.description.comments <p>This preprint was published as Li Ming and William Q. Meeker, "Application of Bayesian Methods in Reliability Data Analyses", <em>Journal of Quality Technology</em> (2014): 1-23.</p>
dc.identifier archive/
dc.identifier.articleid 1083
dc.identifier.contextkey 7436883
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath stat_las_preprints/84
dc.language.iso en
dc.source.bitstream archive/|||Sat Jan 15 02:10:53 UTC 2022
dc.subject.disciplines Statistics and Probability
dc.subject.keywords accelerated test
dc.subject.keywords degradation
dc.subject.keywords MCMC
dc.subject.keywords likelihood
dc.subject.keywords OpenBUGS
dc.subject.keywords prior information
dc.title Application of Bayesian Methods in Reliability Data Analyses
dc.type article
dc.type.genre article
dspace.entity.type Publication
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relation.isOrgUnitOfPublication 264904d9-9e66-4169-8e11-034e537ddbca
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