Please use this identifier to cite or link to this item: https://repositorio.ufrn.br/handle/123456789/49678
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dc.contributor.authorBourguignon, Marcelo-
dc.contributor.authorGhosh, Indranil-
dc.contributor.authorCordeiro, Gauss M.-
dc.date.accessioned2022-11-08T18:23:25Z-
dc.date.available2022-11-08T18:23:25Z-
dc.date.issued2016-
dc.identifier.citationBOURGUIGNON, Marcelo; GHOSH, Indranil; CORDEIRO, Gauss M. . General Results for the Transmuted Family of Distributions and New Models. Journal of Probability and Statistics, v. 2016, p. 1-12, 2016. Disponível em:https://www.hindawi.com/journals/jps/2016/7208425. Acesso em: 07 dez. 2017.pt_BR
dc.identifier.urihttps://repositorio.ufrn.br/handle/123456789/49678-
dc.languageenpt_BR
dc.publisherJournal of Probability and Statisticspt_BR
dc.rightsAcesso Abertopt_BR
dc.subjectTransmuted Familypt_BR
dc.subjectInformation Theorypt_BR
dc.subjectMaximum Likelihood Estimationpt_BR
dc.titleGeneral results for the transmuted Family of distributions and new modelspt_BR
dc.typearticlept_BR
dc.identifier.doihttp://dx.doi.org/10.1155/2016/7208425-
dc.description.resumoThe transmuted family of distributions has been receiving increased attention over the last few years. For a baseline G distribution, we derive a simple representation for the transmuted-G family density function as a linear mixture of the G and exponentiated-G densities. We investigate the asymptotes and shapes and obtain explicit expressions for the ordinary and incomplete moments, quantile and generating functions, mean deviations, R´enyi and Shannon entropies, and order statistics and their moments. We estimate the model parameters of the family by the method of maximum likelihood. We prove empirically the flexibility of the proposed model by means of an application to a real data set.pt_BR
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