Exploring R for Modeling Spatial Extreme Precipitation Data

Natural hazards such as high rainfall and windstorms arise due to physical processes and are usually spatial in its nature. Classical geostatistics, mostly based on multivariate normal distributions, is inappropriate for modeling tail behavior. Several methods have been proposed for the spatial modeling of extremes, among which max-stable processes are perhaps the most well known. They form a natural class of processes extending extreme value theory when sample maxima are observed at each site of a spatial process. Jointly with the theoretical framework for modeling and characterizing measures of dependence of those processes, to deal with free and open-source software is of great value for practitioners. In this note, we illustrate how R can be used for modeling spatial extreme precipitation data.