Tools for the statistical modelling of spatial extremes using max-stable processes, copula or Bayesian hierarchical models. More precisely, this package allows (conditional) simulations from various parametric max-stable models, analysis of the extremal spatial dependence, the fitting of such processes using composite likelihoods or least square (simple max-stable processes only), model checking and selection and prediction. Other approaches (although not completely in agreement with the extreme ...

Goodness-of-fit tests for selection of r in the r-largest order statistics (GEVr) model. Goodness-of-fit tests for threshold selection in the Generalized Pareto distribution (GPD).

Efficient implementations for all the popular synergy scoring models for drug combinations, including HSA, Loewe, Bliss and ZIP and visualization of the synergy scores as either a two-dimensional or a three-dimensional interaction surface over the ...

This package contains code to 1.) construct the summary statistic needed to facilitate approximate Bayesian computing for spatial extremes, and then 2.) run the ABC-Rejection method to produce a set of draws from the ABC posterior. The intention is ...

This package fits a hierarchical spatial model for the generalized extreme value distribution with the option of model averaging over the space of covariates.

Provides functions implementing the pairwise M-estimator for parametric models for stable tail dependence functions described in "An M-estimator of spatial tail dependence" (Einmahl, J.H.J., Kiriliouk, A., Krajina, A. and Segers, J., 2014).