Gamma regression models with the Gammareg R package

Abstract

The class of gamma regression models is based on the assumption that the dependent variable is gamma distributed and that its mean is related to a set of regressors through a linear predictor with unknown coefficients and a link function. This link can be the identity, the inverse or the logarithm function. The model also includes a shape parameter, which may be constant or dependent on a set of regressors through a link function, as the logarithm function. In this paper we describe the Gammareg Rpackage, which provides the class of gamma regressions in the R system for their statistical computing. The underlying theory is briefly presented and the library implementation illustrated from simulation studies.