Load-Sharing Model under Lindley Distribution and Its Parameter Estimation Using the Expectation-Maximization Algorithm

dc.contributor.authorPark, Chanseok
dc.contributor.authorWang, Min
dc.contributor.authorAlotaibi, Refah Mohammed
dc.contributor.authorRezk, Hoda
dc.date.accessioned2021-04-19T15:24:30Z
dc.date.available2021-04-19T15:24:30Z
dc.date.issued2020-11-22
dc.date.updated2021-04-19T15:24:30Z
dc.description.abstractA load-sharing system is defined as a parallel system whose load will be redistributed to its surviving components as each of the components fails in the system. Our focus is on making statistical inference of the parameters associated with the lifetime distribution of each component in the system. In this paper, we introduce a methodology which integrates the conventional procedure under the assumption of the load-sharing system being made up of fundamental hypothetical latent random variables. We then develop an expectation maximization algorithm for performing the maximum likelihood estimation of the system with Lindley-distributed component lifetimes. We adopt several standard simulation techniques to compare the performance of the proposed methodology with the Newton–Raphson-type algorithm for the maximum likelihood estimate of the parameter. Numerical results indicate that the proposed method is more effective by consistently reaching a global maximum.
dc.description.departmentManagement Science and Statistics
dc.identifierdoi: 10.3390/e22111329
dc.identifier.citationEntropy 22 (11): 1329 (2020)
dc.identifier.urihttps://hdl.handle.net/20.500.12588/530
dc.rightsAttribution 4.0 United States
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectexpectation-maximization algorithm
dc.subjecthypothetical latent random variable
dc.subjectLindley distribution
dc.subjectmaximum likelihood estimation
dc.subjectNewton–Raphson method
dc.titleLoad-Sharing Model under Lindley Distribution and Its Parameter Estimation Using the Expectation-Maximization Algorithm
dc.typeArticleen_US

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