Bayesian inference for the Brown-Resnick process, with an application to extreme low temperatures
From MaRDI portal
Publication:512434
DOI10.1214/16-AOAS980zbMath1454.62462arXiv1506.07836MaRDI QIDQ512434
Juha Heikkinen, Daniel Cooley, Juha Aalto, Anthony C. Davison, Emeric Thibaud
Publication date: 24 February 2017
Published in: The Annals of Applied Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1506.07836
partitionmax-stable processglobal warminglikelihood-based inferencenonstationary extremesspace-time declustering
Applications of statistics to environmental and related topics (62P12) Bayesian inference (62F15) Statistics of extreme values; tail inference (62G32) Stable stochastic processes (60G52) Climate science and climate modeling (86A08)
Related Items
Multivariate extremes and max-stable processes: discussion of the paper by Zhengjun Zhang, The realization problem for tail correlation functions, Non-stationary dependence structures for spatial extremes, Consistency of Bayesian inference for multivariate max-stable distributions, A Vecchia approximation for high-dimensional Gaussian cumulative distribution functions arising from spatial data, On the performance of the Bayesian composite likelihood estimation of max-stable processes, Neural networks for parameter estimation in intractable models, A modeler's guide to extreme value software, Truncated pair-wise likelihood for the Brown-Resnick process with applications to maximum temperature data, High-dimensional inference using the extremal skew-\(t\) process, Exploration and inference in spatial extremes using empirical basis functions, Improved return level estimation via a weighted likelihood, latent spatial extremes model, New exploratory tools for extremal dependence: \(\chi \) networks and annual extremal networks, A spatio-temporal model for Red Sea surface temperature anomalies, ABC model selection for spatial extremes models applied to south Australian maximum temperature data, Multivariate modelling of spatial extremes based on copulas, Efficient simulation of Brown‒Resnick processes based on variance reduction of Gaussian processes, Bayesian Model Averaging Over Tree-based Dependence Structures for Multivariate Extremes, Generalised least squares estimation of regularly varying space-time processes based on flexible observation schemes, On logarithmically optimal exact simulation of max-stable and related random fields on a compact set
