Bayesian Model Averaging Over Tree-based Dependence Structures for Multivariate Extremes
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Publication:3391465
DOI10.1080/10618600.2019.1647847OpenAlexW2964764267MaRDI QIDQ3391465
Johan Segers, Raphaël Huser, Marc G. Genton, Sabrina Vettori
Publication date: 28 March 2022
Published in: Journal of Computational and Graphical Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1705.10488
air pollutionreversible jump Markov chain Monte Carloextreme eventfast likelihood inferencenested logistic model
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Cites Work
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- A hierarchical max-stable spatial model for extreme precipitation
- Reversible jump Markov chain Monte Carlo computation and Bayesian model determination
- Bayesian model averaging for multivariate extremes
- Likelihood estimators for multivariate extremes
- Densities of nested Archimedean copulas
- Extremal \(t\) processes: elliptical domain of attraction and a spectral representation
- Efficiently sampling nested Archimedean copulas
- Geostatistics of dependent and asymptotically independent extremes
- Bayesian inference for the Brown-Resnick process, with an application to extreme low temperatures
- On the structure and estimation of hierarchical Archimedean copulas
- A spectral representation for max-stable processes
- Bayesian model averaging: A tutorial. (with comments and a rejoinder).
- Bayesian Dirichlet mixture model for multivariate extremes: a re-parametrization
- Nonparametric estimation of the tree structure of a nested Archimedean copula
- Inference from iterative simulation using multiple sequences
- Simulating multivariate extreme value distributions of logistic type
- Dimension reduction in multivariate extreme value analysis
- Bayesian Inference from Composite Likelihoods, with an Application to Spatial Extremes
- Dependence modelling for spatial extremes
- Likelihood Inference for Multivariate Extreme Value Distributions Whose Spectral Vectors have known Conditional Distributions
- On the likelihood function of Gaussian max-stable processes
- Modelling multivariate extreme value distributions
- Bivariate Exponential Distributions
- On the occurrence times of componentwise maxima and bias in likelihood inference for multivariate max-stable distributions
- A note on composite likelihood inference and model selection
- Statistics for near independence in multivariate extreme values
- Limit theory for multivariate sample extremes
- Non-Parametric Bayesian Inference on Bivariate Extremes
- A Conditional Approach for Multivariate Extreme Values (with Discussion)
- Fisher information for a multivariate extreme value distribution
- Properties of hierarchical Archimedean copulas
- Space–Time Modelling of Extreme Events
- 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
- Exploiting occurrence times in likelihood inference for componentwise maxima
- Geostatistics of extremes
- Modelling Across Extremal Dependence Classes
- Composite likelihood estimation for the Brown-Resnick process
- Monte Carlo sampling methods using Markov chains and their applications
- Decompositions of dependence for high-dimensional extremes
- Statistical modeling of spatial extremes
