Bayesian analysis of masked system lifetime data

  • Yincai Tang*
  • , Ancha Xu
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

In the masked system lifetime data, the exact failure causes are often unknown. For each series system at test, we observe its system's failure time and a set of components that includes the component actually causing the system to fail. The objective is to make inferences for the reliability of the components. In this paper we introduce auxiliary variables to simplify likelihood function. In addition to exponential istributions for the component lifetimes, we also consider Weibull distributions. A Bayesian approach that uses Gibbs sampling will be developed for each of the models.

Original languageEnglish
Title of host publicationProceedings of 2009 8th International Conference on Reliability, Maintainability and Safety, ICRMS 2009
Pages399-402
Number of pages4
DOIs
StatePublished - 2009
Externally publishedYes
Event2009 8th International Conference on Reliability, Maintainability and Safety, ICRMS 2009 - Chengdu, China
Duration: 20 Jul 200924 Jul 2009

Publication series

NameProceedings of 2009 8th International Conference on Reliability, Maintainability and Safety, ICRMS 2009

Conference

Conference2009 8th International Conference on Reliability, Maintainability and Safety, ICRMS 2009
Country/TerritoryChina
CityChengdu
Period20/07/0924/07/09

Keywords

  • Auxiliary variable
  • Bayes estimator
  • Gibbs sampling
  • Weibull distribution

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