Title:	Exponentiated discrete weibull distribution for censored data
Authors:	Cardial, Marcílio Ramos Pereira Gomes, Juliana Betini Fachini Nakano, Eduardo Yoshio
metadata.dc.contributor.affiliation:	Universidade de Brasília Universidade de Brasília Universidade de Brasília
Assunto::	Análise de sobrevivência (Biometria) Distribuição (Probabilidades) Inferência bayesiana
Issue Date:	28-Mar-2020
Publisher:	Editora UFLA
Citation:	CARDIAL, Marcílio Ramos Pereira; FACHINI-GOMES, Juliana Betini; NAKANO, Eduardo Yoshio. Exponentiated discrete weibull distribution for censored data. Brazilian Journal of Biometrics, Lavras, v. 38, n. 1, p. 35–56, 2020. DOI: 10.28951/rbb.v38i1.425. Disponível em: https://biometria.ufla.br/index.php/BBJ/article/view/425. Acesso em: 22 set. 2023.
Abstract:	This paper further develops the statistical inference procedure of the exponentiated discrete Weibull distribution (EDW) for data with the presence of censoring. This generalization of the discrete Weibull distribution has the advantage of being suitable to model non-monotone failure rates, such as those with bathtub and unimodal distributions. Inferences about EDW distribution are presented using both frequentist and bayesian approaches. In addition, the classical Likelihood Ratio Test and a Full Bayesian Significance Test (FBST) were performed to test the parameters of EDW distribution. The method presented is applied to simulated data and illustrated with a real dataset regarding patients diagnosed with head and neck cancer.
metadata.dc.description.unidade:	Instituto de Ciências Exatas (IE) Departamento de Estatística (IE EST)
Licença::	Brazilian Journal of Biometrics All the contents of this journal, except where otherwise noted, is licensed under a Creative Commons Attribution-NonCommercial 4.0 International Public License (CC BY-NC 4.0). Fonte: https://biometria.ufla.br/index.php/BBJ/article/view/425. Acesso em: 22 set. 2023.
DOI:	https://doi.org/10.28951/rbb.v38i1.425
Appears in Collections:	Artigos publicados em periódicos e afins

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