BAYEX: Spatiotemporal Bayesian hierarchical modeling of storm surge extremes with max-stable processes

BAYEX offers spatiotemporal Bayesian hierarchical modeling of storm surge extremes using max-stable and latent processes. As a key feature, BAYEX makes estimates of both the GEV parameters (location, scale and shape) and the annual maxima at any arbitrary location, either gauged or ungauged, while providing realistic uncertainty estimates. Inference in BAYEX is performed using Hamiltonian Monte Carlo as implemented by the Stan probabilistic programming language.This version 1.0 of the code was released to accompany the paper:

Calafat, F. M., and M. Marcos (2020), Probabilistic reanalysis of storm surge extremes in Europe. Proc. Natl. Acad. Sci. U. S. A.

The Bayesian hierarchical model implemented by this code is based on the approach developed in the paper below, but with several modifications to how the spatiotemporal evolution of the GEV parameters is modelled:
Reich, B. J., and B. A. Shaby, A hierarchical max-stable spatial model for extreme precipitation. Ann. Appl. Stat. 6, 1430–1451 (2012).