Classical and Bayesian inference approaches for the exponentiated discrete Weibull model with censored data and a cure fraction

Autor:	Edson Zangiacomi Martinez, Bruno Caparroz Lopes de Freitas, Marcos Vinicius de Oliveira Peres, Jorge Alberto Achcar
Rok vydání:	2021
Předmět:	Statistics and Probability INFERÊNCIA BAYESIANA Modeling and Simulation Applied mathematics Fraction (mathematics) Management Science and Operations Research Statistics Probability and Uncertainty Bayesian inference Mathematics Weibull distribution
Zdroj:	Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual) Universidade de São Paulo (USP) instacron:USP
ISSN:	2220-5810 1816-2711
Popis:	In this paper, we introduce maximum likelihood and Bayesian parameter estimation for the exponentiated discrete Weibull (EDW) distribution in presence of randomly right censored data. We also consider the inclusion of a cure fraction in the model. The performance of the maximum likelihood estimation approach is assessed by conducting an extensive simulation study with different sample sizes and different values for the parameters of the EDW distribution. The usefuness of the proposed model is illustrated with two examples considering real data sets.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::da2a46074ed23325b71d5cf1a2d0c47c https://doi.org/10.18187/pjsor.v17i2.3693 Zobrazit plný text záznamu