Quantile Regression with a New Exponentiated Odd Log-Logistic Weibull Distribution

Gabriela M. Rodrigues, Edwin M. M. Ortega (), Gauss M. Cordeiro and Roberto Vila
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Gabriela M. Rodrigues: Department of Exact Sciences, University of São Paulo, Piracicaba 13418-900, Brazil
Edwin M. M. Ortega: Department of Exact Sciences, University of São Paulo, Piracicaba 13418-900, Brazil
Gauss M. Cordeiro: Department of Statistics, Federal University of Pernambuco, Recife 50670-901, Brazil
Roberto Vila: Department of Statistics, University of Brasilia, Brasilia 70910-900, Brazil

Mathematics, 2023, vol. 11, issue 6, 1-20

Abstract: We define a new quantile regression model based on a reparameterized exponentiated odd log-logistic Weibull distribution, and obtain some of its structural properties. It includes as sub-models some known regression models that can be utilized in many areas. The maximum likelihood method is adopted to estimate the parameters, and several simulations are performed to study the finite sample properties of the maximum likelihood estimators. The applicability of the proposed regression model is well justified by means of a gastric carcinoma dataset.

Keywords: censored data; hazard function; odd log-logistic Weibull; statistical reparameterization; survival function (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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