Modeling spatial tail dependence with Cauchy convolution processes
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Publication:2106793
DOI10.1214/22-EJS2081MaRDI QIDQ2106793
Publication date: 19 December 2022
Published in: Electronic Journal of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2102.07094
copulatail dependencespatial processextreme-value modelkernel convolution processshort-range spatial dependence
Directional data; spatial statistics (62H11) Characterization and structure theory for multivariate probability distributions; copulas (62H05) Extreme value theory; extremal stochastic processes (60G70)
Cites Work
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- Pair-copula constructions of multiple dependence
- Non-stationary dependence structures for spatial extremes
- Factor copula models for multivariate data
- A highly efficient L-estimator for the location parameter of the Cauchy distribution
- Rank-based inference for bivariate extreme-value copulas
- Stationary max-stable fields associated to negative definite functions
- A spectral representation for max-stable processes
- Extremes of moving averages of stable processes
- Models for stationary max-stable random fields
- Statistical post-processing of forecasts for extremes using bivariate Brown-Resnick processes with an application to wind gusts
- A general approach to full-range tail dependence copulas
- On a bivariate copula with both upper and lower full-range tail dependence
- Multivariate peaks over thresholds models
- A copula model for non-Gaussian multivariate spatial data
- Maxima of normal random vectors: Between independence and complete dependence
- Estimating high-resolution red sea surface temperature hotspots, using a low-rank semiparametric spatial model
- Tail correlation functions of max-stable processes
- Lévy-based Modelling in Brain Imaging
- Dependence modelling for spatial extremes
- Max-stable models for multivariate extremes
- Handbook of Environmental and Ecological Statistics
- Bayesian Model Averaging Over Tree-based Dependence Structures for Multivariate Extremes
- R‐vine models for spatial time series with an application to daily mean temperature
- A General Approach to the Optimality of Minimum Distance Estimators
- Statistics for near independence in multivariate extreme values
- Nonseparable, Stationary Covariance Functions for Space–Time Data
- High-dimensional peaks-over-threshold inference
- Tail-weighted dependence measures with limit being the tail dependence coefficient
- Linear factor copula models and their properties
- Factor Copula Models for Replicated Spatial Data
- Max‐infinitely divisible models and inference for spatial extremes
- Graphical Models for Extremes
- Space–Time Modelling of Extreme Events
- Local Likelihood Estimation of Complex Tail Dependence Structures, Applied to U.S. Precipitation Extremes
- Bayesian modeling of air pollution extremes using nested multivariate max‐stable processes
- Modeling Spatial Processes with Unknown Extremal Dependence Class
- Likelihood-Based Inference for Max-Stable Processes
- Geostatistics of extremes
- Modelling Across Extremal Dependence Classes
- Estimation of Hüsler–Reiss Distributions and Brown–Resnick Processes
- Extremes of regularly varying Lévy-driven mixed moving average processes
- A Multivariate Exponential Distribution
- A Hierarchical Max-Infinitely Divisible Spatial Model for Extreme Precipitation
- Statistical modeling of spatial extremes
