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dc.contributor.authorDey, Sanku
dc.contributor.authorMoala, Fernando Antonio [UNESP]
dc.identifier.citationInternational Journal Of Quality & Reliability Management. Bingley: Emerald Group Publishing Ltd, v. 36, n. 2, p. 122-136, 2019.
dc.description.abstractPurpose The purpose of this paper is to deal with the Bayesian and non-Bayesian estimation methods of multicomponent stress-strength reliability by assuming the Chen distribution. Design/methodology/approach The reliability of a multicomponent stress-strength system is obtained by the maximum likelihood (MLE) and Bayesian methods and the results are compared by using MCMC technique for both small and large samples. Findings The simulation study shows that Bayes estimates based on gamma prior with absence of prior information performs little better than the MLE with regard to both biases and mean squared errors. The Bayes credible intervals for reliability are also shorter length with competitive coverage percentages than the condence intervals. Further, the coverage probability is quite close to the nominal value in all sets of parameters when both sample sizes n and m increases. Originality/value The lifetime distributions used in reliability analysis as exponential, gamma, lognormal and Weibull only exhibit monotonically increasing, decreasing or constant hazard rates. However, in many applications in reliability and survival analysis, the most realistic hazard rate is bathtub-shaped found in the Chen distribution. Therefore, the authors have studied the multicomponent stress-strength reliability under the Chen distribution by comparing the MLE and Bayes estimators.en
dc.publisherEmerald Group Publishing Ltd
dc.relation.ispartofInternational Journal Of Quality & Reliability Management
dc.sourceWeb of Science
dc.subjectBayesian estimation
dc.subjectMaximum likelihood estimation
dc.subjectChen distribution
dc.subjectReliability of multicomponent
dc.titleEstimation of reliability of multicomponent stress-strength of a bathtub shape or increasing failure rate functionen
dcterms.rightsHolderEmerald Group Publishing Ltd
dc.contributor.institutionSt Anthony Coll
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.description.affiliationSt Anthony Coll, Dept Stat, Shillong, Meghalaya, India
dc.description.affiliationUniv Estadual Paulista Portal, Dept Stat, Presidente Prudente, Brazil
dc.description.affiliationUnespUniv Estadual Paulista Portal, Dept Stat, Presidente Prudente, Brazil
dc.rights.accessRightsAcesso aberto
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