A Vecchia approximation for high-dimensional Gaussian cumulative distribution functions arising from spatial data

DOI10.1080/00949655.2021.2016759OpenAlexW3045941984MaRDI QIDQ5086084

Benjamin A. Shaby, Mauricio Nascimento

Publication date: 1 July 2022

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2007.15195

zbMATH Keywords

Gaussian processspatial extremesscale mixture

Mathematics Subject Classification ID

Statistics (62-XX)

Uses Software

• R
• QSIMVN
• mvPot

Cites Work

• Likelihood estimators for multivariate extremes
• Bayesian inference for the Brown-Resnick process, with an application to extreme low temperatures
• Computation of multivariate normal and \(t\) probabilities
• Extremal dependence of random scale constructions
• Hierarchical-block conditioning approximations for high-dimensional multivariate normal probabilities
• Hierarchical Matrices: Algorithms and Analysis
• Hierarchical Decompositions for the Computation of High-Dimensional Multivariate Normal Probabilities
• On the Unification of Families of Skew-normal Distributions
• High-dimensional peaks-over-threshold inference
• Approximating Likelihoods for Large Spatial Data Sets
• The Evaluation of General Non-Centred Orthant Probabilities
• Modeling Spatial Processes with Unknown Extremal Dependence Class
• Efficient inference for spatial extreme value processes associated to log-Gaussian random functions
• A Space-Time Skew-t Model for Threshold Exceedances

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