A new truncated lindley-generated family of distributions : properties, regression analysis, and applications

Hussein, Mohamed; Rodrigues, Gabriela Maria; Ortega, Edwin M. M.; Vila, Roberto; Elsayed, Howaida

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Campo DC	Valor	Lengua/Idioma
dc.contributor.author	Hussein, Mohamed	-
dc.contributor.author	Rodrigues, Gabriela Maria	-
dc.contributor.author	Ortega, Edwin M. M.	-
dc.contributor.author	Vila, Roberto	-
dc.contributor.author	Elsayed, Howaida	-
dc.date.accessioned	2024-06-25T11:56:11Z	-
dc.date.available	2024-06-25T11:56:11Z	-
dc.date.issued	2023	-
dc.identifier.citation	HUSSEIN, 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.uri	http://repositorio2.unb.br/jspui/handle/10482/48398	-
dc.language.iso	eng	pt_BR
dc.publisher	MDPI	pt_BR
dc.rights	Acesso Aberto	pt_BR
dc.title	A new truncated lindley-generated family of distributions : properties, regression analysis, and applications	pt_BR
dc.type	Artigo	pt_BR
dc.subject.keyword	Dados censurados	pt_BR
dc.subject.keyword	Análise de sobrevivência	pt_BR
dc.subject.keyword	Máxima verossimilhança	pt_BR
dc.subject.keyword	Covid-19	pt_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.doi	https://doi.org/10.3390/e25091359	pt_BR
dc.description.abstract1	We 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.orcid	https://orcid.org/0000-0002-7332-0334	pt_BR
dc.identifier.orcid	https://orcid.org/0000-0002-1985-8141	pt_BR
dc.identifier.orcid	https://orcid.org/0000-0003-3999-7402	pt_BR
dc.identifier.orcid	https://orcid.org/0000-0003-1073-0114	pt_BR
dc.identifier.orcid	https://orcid.org/0000-0003-1323-5346	pt_BR
dc.contributor.affiliation	Alexandria University, Department of Mathematics and Computer Science	pt_BR
dc.contributor.affiliation	King Khalid University, College of Business, Department of Business Administration	pt_BR
dc.contributor.affiliation	University of São Paulo, Piracicaba, Department of Exact Sciences	pt_BR
dc.contributor.affiliation	University of Brasilia, Department of Statistics	pt_BR
dc.contributor.affiliation	King Khalid University, College of Business, Department of Business Administration	pt_BR
dc.description.unidade	Instituto de Ciências Exatas (IE)	pt_BR
dc.description.unidade	Departamento de Estatística (IE EST)	pt_BR
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