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.ME2019
Approximate Bayesian inference for analysis of spatio-temporal flood frequency data
Árni V. Johannesson, Stefan Siegert, Raphaël Huser +2
Extreme floods cause casualties, and widespread damage to property and vital civil infrastructure. We here propose a Bayesian approach for predicting extreme floods using the gener…