Continuous spatial process models for spatial extreme values
From MaRDI portal
Publication:2260130
DOI10.1007/s13253-009-0010-1zbMath1306.62334OpenAlexW4367011210MaRDI QIDQ2260130
Publication date: 5 March 2015
Published in: Journal of Agricultural, Biological, and Environmental Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s13253-009-0010-1
generalized extreme value distributionspatial interpolationcopula Gaussian process modelsmaximum precipitation surfaces
Inference from spatial processes (62M30) Applications of statistics to environmental and related topics (62P12) Statistics of extreme values; tail inference (62G32)
Related Items
Investigating precipitation extremes in South Carolina with focus on the state's October 2015 precipitation event, Approximate Bayesian inference for analysis of spatiotemporal flood frequency data, A Bayesian hierarchical model for spatial extremes with multiple durations, Spatial generalized linear models with non-Gaussian translation processes, Spatial extreme value analysis to project extremes of large‐scale indicators for severe weather, Assessing exceedance of ozone standards: a space‐time downscaler for fourth highest ozone concentrations, Spatial modelling framework for the characterisation of rainfall extremes at different durations and under climate change, Projecting flood-inducing precipitation with a Bayesian analogue model, Extreme value and cluster analysis of European daily temperature series, Spatial modeling of extreme snow depth, A spatio-temporal dynamic regression model for extreme wind speeds, Geostatistics of dependent and asymptotically independent extremes, Estimating high-resolution red sea surface temperature hotspots, using a low-rank semiparametric spatial model, Spatio-temporal modelling of extreme storms, A hierarchical max-stable spatial model for extreme precipitation, Assessing the risk of disruption of wind turbine operations in Saudi Arabia using Bayesian spatial extremes, Statistical modeling of spatial extremes, Discussion of ``Statistical modeling of spatial extremes by A. C. Davison, S. A. Padoan and M. Ribatet, Rejoinder, Spatial Bayesian Nonparametric Methods, Generalized Additive Models for Exceedances of High Thresholds With an Application to Return Level Estimation for U.S. Wind Gusts, Multivariate modelling of spatial extremes based on copulas, CAN A REGIONAL CLIMATE MODEL REPRODUCE OBSERVED EXTREME TEMPERATURES, A Hierarchical Max-Infinitely Divisible Spatial Model for Extreme Precipitation, Modelling sub-daily precipitation extremes with the blended generalised extreme value distribution, A flexible dependence model for spatial extremes
Uses Software
Cites Work
- An introduction to copulas.
- Interpolation of spatial data. Some theory for kriging
- Langevin-type models II: Self-targeting candidates for MCMC algorithms
- On spatial extremes: with application to a rainfall problem
- Spatial extremes: models for the stationary case
- Sampling-Based Approaches to Calculating Marginal Densities
- Bayesian Spatial Modeling of Extreme Precipitation Return Levels
- Statistics for near independence in multivariate extreme values
- Model-Based Geostatistics
- A dependence measure for multivariate and spatial extreme values: Properties and inference
- A Conditional Approach for Multivariate Extreme Values (with Discussion)
- Statistics of Extremes
- Inconsistent Estimation and Asymptotically Equal Interpolations in Model-Based Geostatistics
- Space–Time Covariance Functions
- An introduction to statistical modeling of extreme values
- Dependence measures for extreme value analyses
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
