dc.contributorTanta Univ
dc.contributorUniversidade Estadual Paulista (Unesp)
dc.contributorKohat Univ Sci & Technol
dc.date.accessioned2020-12-10T16:57:45Z
dc.date.accessioned2022-12-19T19:57:45Z
dc.date.available2020-12-10T16:57:45Z
dc.date.available2022-12-19T19:57:45Z
dc.date.created2020-12-10T16:57:45Z
dc.date.issued2019-10-01
dc.identifierMathematica Slovaca. Berlin: Walter De Gruyter Gmbh, v. 69, n. 5, p. 1185-1212, 2019.
dc.identifier0139-9918
dc.identifierhttp://hdl.handle.net/11449/194888
dc.identifier10.1515/ms-2017-0300
dc.identifierWOS:000489303400021
dc.identifier1621269552366697
dc.identifier0000-0002-2445-0407
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/5375525
dc.description.abstractIn this paper, we introduce a new bivariate Kumaraswamy exponential distribution, whose marginals are univariate Kumaraswamy exponential. Some probabilistic properties of this bivariate distribution are derived, such as joint density function, marginal density functions, conditional density functions, moments and stress-strength reliability. Also, we provide the expected information matrix with its elements in a closed form. Estimation of the parameters is investigated by the maximum likelihood, Bayesian and least squares estimation methods. A simulation study is carried out to compare the performance of the estimators by estimation methods. Further, one data set have been analyzed to show how the proposed distribution works in practice. (C) 2019 Mathematical Institute Slovak Academy of Sciences
dc.languageeng
dc.publisherWalter De Gruyter Gmbh
dc.relationMathematica Slovaca
dc.sourceWeb of Science
dc.subjectbivariate Kumaraswamy-exponential distribution
dc.subjectmarginal and conditional density functions
dc.subjectmoments
dc.subjectstress-strength
dc.subjectmaximum likelihood
dc.subjectFisher information matrix
dc.subjectBayesian estimation
dc.titleA BIVARIATE KUMARASWAMY-EXPONENTIAL DISTRIBUTION WITH APPLICATION
dc.typeArtículos de revistas


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