On gamma regression residuals (2019)
In this paper we propose a new residuals for gamma regression models, assuming that both mean and shape parameters, follow regression structures. The models are summarized and fitted by applying both classic and Bayesian methods as proposed by Cepeda-Cuervo. The residuals are proposed from properties of the biparametric exponential family of distributions and simulated and real data sets are analyzed to determine the performance and behavior of the proposed residuals.