Distributional regression models for Extended Generalized Pareto distributions

The Extended Generalized Pareto Distribution (EGPD) (Naveau et al. 2016) is a family of distribution that has been introduced to model the full range of a positive random variable but with the lower and the upper tails distributed according to the peaks-over-threshold methodology. The aim of this article is to augment the scope of application of EGPD allowing the analyst to incorporate the effect of covariates on the model. In particular we introduce a specification where the parameters of EGPD can be modeled as additive functions of the covariates, e.g. space or time. As a related product we provide an add-on code written in R that it is flexible enough to implement the EGPD in a generic way, allowing to introduce new parametric forms. We show the potential of our add-on on the modeling of hourly rainfalls over the North-West region of France and discuss modeling strategies.