6 papers · 1 filter
Tractable Bayes of Skew-Elliptical Link Models for Correlated Binary Data
Zhongwei Zhang, Reinaldo B. Arellano-Valle, Marc G. Genton +1
Correlated binary response data with covariates are ubiquitous in longitudinal or spatial studies. Among the existing statistical models the most well-known one for this type of da…
Advances in Statistical Modeling of Spatial Extremes
Raphaël Huser, Jennifer L. Wadsworth
The classical modeling of spatial extremes relies on asymptotic models (i.e., max-stable processes or -Pareto processes) for block maxima or peaks over high thresholds, respecti…
Modeling Non-Stationary Temperature Maxima Based on Extremal Dependence Changing with Event Magnitude
Peng Zhong, Raphaël Huser, Thomas Opitz
The modeling of spatio-temporal trends in temperature extremes can help better understand the structure and frequency of heatwaves in a changing climate. Here, we study annual temp…
Spatial hierarchical modeling of threshold exceedances using rate mixtures
Rishikesh Yadav, Raphaël Huser, Thomas Opitz
We develop new flexible univariate models for light-tailed and heavy-tailed data, which extend a hierarchical representation of the generalized Pareto (GP) limit for threshold exce…
Asymmetric tail dependence modeling, with application to cryptocurrency market data
Yan Gong, Raphaël Huser
Since the inception of Bitcoin in 2008, cryptocurrencies have played an increasing role in the world of e-commerce, but the recent turbulence in the cryptocurrency market in 2018 h…
INLA goes extreme: Bayesian tail regression for the estimation of high spatio-temporal quantiles
Thomas Opitz, Raphaël Huser, Haakon Bakka +1
This work has been motivated by the challenge of the 2017 conference on Extreme-Value Analysis (EVA2017), with the goal of predicting daily precipitation quantiles at the …