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dc.contributor.authorHussein, Mohamed-
dc.contributor.authorRodrigues, Gabriela Maria-
dc.contributor.authorOrtega, Edwin M. M.-
dc.contributor.authorVila, Roberto-
dc.contributor.authorElsayed, Howaida-
dc.date.accessioned2024-06-25T11:56:11Z-
dc.date.available2024-06-25T11:56:11Z-
dc.date.issued2023-
dc.identifier.citationHUSSEIN, Mohamed et al. A new truncated lindley-generated family of distributions: properties, regression analysis, and applications. Entropy, [S. l.], v. 25, n. 9, 1359, 2023. DOI: https://doi.org/10.3390/e25091359. Disponível em: https://www.mdpi.com/1099-4300/25/9/1359. Acesso em: 25 jun. 2024.pt_BR
dc.identifier.urihttp://repositorio2.unb.br/jspui/handle/10482/48398-
dc.language.isoengpt_BR
dc.publisherMDPIpt_BR
dc.rightsAcesso Abertopt_BR
dc.titleA new truncated lindley-generated family of distributions : properties, regression analysis, and applicationspt_BR
dc.typeArtigopt_BR
dc.subject.keywordDados censuradospt_BR
dc.subject.keywordAnálise de sobrevivênciapt_BR
dc.subject.keywordMáxima verossimilhançapt_BR
dc.subject.keywordCovid-19pt_BR
dc.rights.license© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).pt_BR
dc.identifier.doihttps://doi.org/10.3390/e25091359pt_BR
dc.description.abstract1We present the truncated Lindley-G (TLG) model, a novel class of probability distributions with an additional shape parameter, by composing a unit distribution called the truncated Lindley distribution with a parent distribution function 𝐺(𝑥). The proposed model’s characteristics including critical points, moments, generating function, quantile function, mean deviations, and entropy are discussed. Also, we introduce a regression model based on the truncated Lindley–Weibull distribution considering two systematic components. The model parameters are estimated using the maximum likelihood method. In order to investigate the behavior of the estimators, some simulations are run for various parameter settings, censoring percentages, and sample sizes. Four real datasets are used to demonstrate the new model’s potential.pt_BR
dc.identifier.orcidhttps://orcid.org/0000-0002-7332-0334pt_BR
dc.identifier.orcidhttps://orcid.org/0000-0002-1985-8141pt_BR
dc.identifier.orcidhttps://orcid.org/0000-0003-3999-7402pt_BR
dc.identifier.orcidhttps://orcid.org/0000-0003-1073-0114pt_BR
dc.identifier.orcidhttps://orcid.org/0000-0003-1323-5346pt_BR
dc.contributor.affiliationAlexandria University, Department of Mathematics and Computer Sciencept_BR
dc.contributor.affiliationKing Khalid University, College of Business, Department of Business Administrationpt_BR
dc.contributor.affiliationUniversity of São Paulo, Piracicaba, Department of Exact Sciencespt_BR
dc.contributor.affiliationUniversity of Brasilia, Department of Statisticspt_BR
dc.contributor.affiliationKing Khalid University, College of Business, Department of Business Administrationpt_BR
dc.description.unidadeInstituto de Ciências Exatas (IE)pt_BR
dc.description.unidadeDepartamento de Estatística (IE EST)pt_BR
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