Estimation of multicomponent stress-strength reliability from exponentiated inverse Rayleigh distribution

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dc.creatorRao, G. S
dc.creatorMbwambo, Sauda
dc.creatorak, Abbas P
dc.creatorPak, Abbas
dc.date2020-11-25T07:50:34Z
dc.date2020-11-25T07:50:34Z
dc.date2020
dc.date.accessioned2022-10-20T13:09:19Z
dc.date.available2022-10-20T13:09:19Z
dc.descriptionAbstract. Full text available at https://doi.org/10.1080/09720510.2020.1761094
dc.descriptionThis paper deals with the classical and Bayesian estimation of multicomponent stress-strength reliability through assuming the exponentiated inverse Rayleigh distribution. Assuming that both stress and strength variates are follows to exponentiated inverse Rayleigh distribution with common and known shape parameter. The multicomponent stress-strength reliability of a system is obtained by the methods of maximum likelihood and Bayesian approach. The results are compared using Markov Chain Monte Carlo (MCMC) technique for both small and large samples. Finally, two data sets of coating weights of iron sheets are analyzed for illustrative purposes.
dc.identifierRao, G.S., Mbwambo, S., & Pak, A. (2020). Estimation of multicomponent stress-strength reliability from exponentiated inverse Rayleigh distribution. Journal of Statistics and Management Systems, 1-21.
dc.identifierDOI: 10.1080/09720510.2020.1761094
dc.identifierhttp://hdl.handle.net/20.500.12661/2604
dc.identifier.urihttp://hdl.handle.net/20.500.12661/2604
dc.languageen
dc.publisherTaylor & Francis
dc.subjectBayesian estimation
dc.subjectMaximum likelihood estimation
dc.subjectML estimation
dc.subjectRayleigh distribution
dc.subjectMulticomponent stress-strength reliability
dc.subjectMarkov Chain Monte Carlo
dc.subjectMCMC
dc.subjectExponentiated inverse rayleigh distribution
dc.subjectBayesian
dc.subjectParameter
dc.titleEstimation of multicomponent stress-strength reliability from exponentiated inverse Rayleigh distribution
dc.typeArticle

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