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

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dc.creator Rao, G. S
dc.creator Mbwambo, Sauda
dc.creator ak, Abbas P
dc.creator Pak, Abbas
dc.date 2020-11-25T07:50:34Z
dc.date 2020-11-25T07:50:34Z
dc.date 2020
dc.date.accessioned 2022-10-20T13:09:19Z
dc.date.available 2022-10-20T13:09:19Z
dc.identifier Rao, 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.identifier DOI: 10.1080/09720510.2020.1761094
dc.identifier http://hdl.handle.net/20.500.12661/2604
dc.identifier.uri http://hdl.handle.net/20.500.12661/2604
dc.description Abstract. Full text available at https://doi.org/10.1080/09720510.2020.1761094
dc.description This 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.language en
dc.publisher Taylor & Francis
dc.subject Bayesian estimation
dc.subject Maximum likelihood estimation
dc.subject ML estimation
dc.subject Rayleigh distribution
dc.subject Multicomponent stress-strength reliability
dc.subject Markov Chain Monte Carlo
dc.subject MCMC
dc.subject Exponentiated inverse rayleigh distribution
dc.subject Bayesian
dc.subject Parameter
dc.title Estimation of multicomponent stress-strength reliability from exponentiated inverse Rayleigh distribution
dc.type Article


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