A Hierarchical Weibull Bayesian Model for Series and Parallel Systems

F. L. Bhering, A. Polpo, C. A. de B. Pereira

Research output: Chapter in Book/Conference paperConference paperpeer-review

Abstract

In this paper we present a hierarchical Bayesian approach to the estimation of component's reliability in a series and parallel systems using the Weibull model. The reliability problem of a series system is similar to the survival problem of right-censored data, while the parallel system is related to left-censored data. We used the Weibull model for the reliability time and a gamma distribution for first level on hierarchy for both, scale and shape, parameters of the model. The estimation is done using Monte Carlo Markov Chain tools and Expectation-Maximization algorithm. To exemplify the efficiency of the model we presented an study with simulated data.

Original languageEnglish
Title of host publicationXI BRAZILIAN MEETING ON BAYESIAN STATISTICS (EBEB 2012)
EditorsJM Stern, MD Lauretto, A Polpo, MA Diniz
PublisherAmerican Institute of Physics
Pages59-66
Number of pages8
DOIs
Publication statusPublished - 2012
Externally publishedYes
Event11th Brazilian Meeting on Bayesian Statistics (EBEB) - São Paulo, Brazil
Duration: 18 Mar 201222 Mar 2012

Publication series

NameAIP Conference Proceedings
PublisherAMER INST PHYSICS
Volume1490
ISSN (Print)0094-243X

Conference

Conference11th Brazilian Meeting on Bayesian Statistics (EBEB)
Country/TerritoryBrazil
CitySão Paulo
Period18/03/1222/03/12

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