Spatial extreme value analysis to project extremes of large‐scale indicators for severe weather

Cites Work

Unnamed Item
Unnamed Item
Unnamed Item
Unnamed Item
Unnamed Item
A hierarchical max-stable spatial model for extreme precipitation
Geostatistics of dependent and asymptotically independent extremes
Asymptotic models and inference for extremes of spatio-temporal data
Multivariate generalized Pareto distributions
A flexible extreme value mixture model
Nonparametric spatial models for extremes: application to extreme temperature data
Vector generalized linear and additive extreme value models
An extended Gaussian max-stable process model for spatial extremes
Resampling methods for dependent data
Estimation of the conditional distribution of a multivariate variable given that one of its components is large: additional constraints for the Heffernan and Tawn model
Continuous spatial process models for spatial extreme values
Spatial hierarchical modeling of precipitation extremes from a regional climate model
On spatial extremes: with application to a rainfall problem
Limit laws for random vectors with an extreme component
Bayesian Inference from Composite Likelihoods, with an Application to Spatial Extremes
Dependence modelling for spatial extremes
On the likelihood function of Gaussian max-stable processes
On the structure and representations of max-stable processes
A Hierarchical Model for Extreme Wind Speeds
Bayesian Spatial Modeling of Extreme Precipitation Return Levels
False Discovery Rates for Spatial Signals
A Conditional Approach for Multivariate Extreme Values (with Discussion)
Environmental Statistics
Statistical Methods for Multivariate Extremes: An Application to Structural Design
Likelihood-Based Inference for Max-Stable Processes
An introduction to statistical modeling of extreme values
Statistical modeling of spatial extremes

This page was built for publication: Spatial extreme value analysis to project extremes of large‐scale indicators for severe weather