A Bayesian spatio-temporal model for precipitation extremes -- STOR team contribution to the EVA2017 challenge
DOI10.1007/s10687-018-0330-zzbMath1404.62133OpenAlexW2809413761MaRDI QIDQ1792629
Emma S. Simpson, Christian Rohrbeck, Anna Maria Barlow, Paul Sharkey, Rob Shooter
Publication date: 12 October 2018
Published in: Extremes (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10687-018-0330-z
extreme value analysisMarkov chain Monte Carlospatio-temporal dependenceprecipitation extremesBayesian hierarchical modelling
Inference from spatial processes (62M30) Asymptotic distribution theory in statistics (62E20) Applications of statistics to environmental and related topics (62P12) Bayesian inference (62F15) Statistics of extreme values; tail inference (62G32)
Related Items (1)
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- A hierarchical max-stable spatial model for extreme precipitation
- Accounting for choice of measurement scale in extreme value modeling
- A flexible extreme value mixture model
- A spectral representation for max-stable processes
- Statistical inference using extreme order statistics
- Weak convergence and optimal scaling of random walk Metropolis algorithms
- Models for stationary max-stable random fields
- A dynamical mixture model for unsupervised tail estimation without threshold selection
- Editorial: Special issue on the extreme value analysis conference challenge ``prediction of extremal precipitation
- Bayesian analysis of extreme events with threshold estimation
- A Hierarchical Model for Extreme Wind Speeds
- Bayesian Spatial Modeling of Extreme Precipitation Return Levels
- Extreme values of independent stochastic processes
- Model-Based Geostatistics
- An introduction to statistical modeling of extreme values
- Statistical modeling of spatial extremes
This page was built for publication: A Bayesian spatio-temporal model for precipitation extremes -- STOR team contribution to the EVA2017 challenge
