A bimodal gamma distribution: Properties, regression model and applications
Abstract
In this paper we propose a bimodal gamma distribution using a quadratic transformation based on the alpha-skew-normal model. We discuss several properties of this distribution such as mean, variance, moments, hazard rate and entropy measures. Further, we propose a new regression model with censored data based on the bimodal gamma distribution. This regression model can be very useful to the analysis of real data and could give more realistic fits than other special regression models. Monte Carlo simulations were performed to check the bias in the maximum likelihood estimation. The proposed models are applied to two real data sets found in literature.
Cite
@article{arxiv.2004.12491,
title = {A bimodal gamma distribution: Properties, regression model and applications},
author = {R. Vila and L. Ferreira and H. Saulo and F. Prataviera and E. M. M. Ortega},
journal= {arXiv preprint arXiv:2004.12491},
year = {2020}
}
Comments
26 pages, 13 figures. Accepted for publication in Statistics: A Journal of Theoretical and Applied Statistics