The Reparametrized Exponentiated-G Distribution Family: Properties and Applications: Accepted - September 2024

Benedito  Vicente dos Santos; Manoel  Santos-Neto; Francisco José A. Cysneiros

doi:10.57805/revstat.vi.791

Forthcoming

The Reparametrized Exponentiated-G Distribution Family: Properties and Applications

Accepted - September 2024

Authors

Benedito Vicente dos Santos Federal University of Pernambuco https://orcid.org/0000-0002-7594-3420
Manoel Santos-Neto Federal University of Ceara https://orcid.org/0000-0002-9007-0680
Francisco José A. Cysneiros Federal University of Pernambuco https://orcid.org/0000-0001-6757-6969

DOI:

https://doi.org/10.57805/revstat.vi.791

Keywords:

baseline distribution, reparametrized exponentiated-G distribution, quantile, maximum likelihood estimator, Monte Carlo simulation

Abstract

The main objective of this paper is to introduce the reparametrized exponentiated-G distribution family and outline its general mathematical properties. In contrast to the exponentiated-G distribution, this reparametrized family is characterized by a parameter {$\eta_\tau$}, which offers an interpretation based on the $\tau$th quantile of the distribution. To illustrate the derivation of submodels within the reparametrized exponentiated-G distribution family, we employed the reparameterized Weibull model as baseline, resulting in the reparameterized exponentiated Weibull model.

Downloads

FP_REVSTAT2024_out2

Published

2024-11-22

How to Cite

Vicente dos Santos, B., Santos-Neto, M. ., & A. Cysneiros, F. J. (2024). The Reparametrized Exponentiated-G Distribution Family: Properties and Applications: Accepted - September 2024. REVSTAT-Statistical Journal. https://doi.org/10.57805/revstat.vi.791