2 papers
stat.ME2019
Max-and-Smooth: a two-step approach for approximate Bayesian inference in latent Gaussian models
Birgir Hrafnkelsson, Stefan Siegert, Raphaël Huser +2
With modern high-dimensional data, complex statistical models are necessary, requiring computationally feasible inference schemes. We introduce Max-and-Smooth, an approximate Bayes…
stat.AP2018
A Hierarchical Max-Infinitely Divisible Spatial Model for Extreme Precipitation
Gregory P. Bopp, Benjamin A. Shaby, Raphaël Huser
Understanding the spatial extent of extreme precipitation is necessary for determining flood risk and adequately designing infrastructure (e.g., stormwater pipes) to withstand such…