102 citations · 151 across the 5 of their papers we have counts for
7 papers
Exploration and inference in spatial extremes using empirical basis functions
Samuel A. Morris, Brian J. Reich, Emeric Thibaud
Statistical methods for inference on spatial extremes of large datasets are yet to be developed. Motivated by standard dimension reduction techniques used in spatial statistics, we…
Max-infinitely divisible models and inference for spatial extremes
Raphael Huser, Thomas Opitz, Emeric Thibaud
For many environmental processes, recent studies have shown that the dependence strength is decreasing when quantile levels increase. This implies that the popular max-stable model…
A Nonparametric Method for Producing Isolines of Bivariate Exceedance Probabilities
Daniel Cooley, Emeric Thibaud, Federico Castillo +1
We present a method for drawing isolines indicating regions of equal joint exceedance probability for bivariate data. The method relies on bivariate regular variation, a dependence…
Decompositions of Dependence for High-Dimensional Extremes
Daniel Cooley, Emeric Thibaud
Employing the framework of regular variation, we propose two decompositions which help to summarize and describel high-dimensional tail dependence. Via transformation, we define a…
Bridging Asymptotic Independence and Dependence in Spatial Extremes Using Gaussian Scale Mixtures
Raphael Huser, Thomas Opitz, Emeric Thibaud
Gaussian scale mixtures are constructed as Gaussian processes with a random variance. They have non-Gaussian marginals and can exhibit asymptotic dependence unlike Gaussian process…
Bayesian inference for the Brown-Resnick process, with an application to extreme low temperatures
Emeric Thibaud, Juha Aalto, Daniel S. Cooley +2
The Brown-Resnick max-stable process has proven to be well-suited for modeling extremes of complex environmental processes, but in many applications its likelihood function is intr…