INLA goes extreme: Bayesian tail regression for the estimation of high spatio-temporal quantiles
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Publication:1792632
DOI10.1007/s10687-018-0324-xzbMath1407.62167arXiv1802.01085OpenAlexW2963225703WikidataQ129768344 ScholiaQ129768344MaRDI QIDQ1792632
Thomas Opitz, Håvard Rue, Haakon Bakka, Raphaël Huser
Publication date: 12 October 2018
Published in: Extremes (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1802.01085
extreme-value theorygeneralized Pareto distributionintegrated nested Laplace approximation (INLA)Bayesian hierarchical modelingextreme-value analysis conference challengehigh quantile estimation
Inference from spatial processes (62M30) Applications of statistics to environmental and related topics (62P12) Bayesian inference (62F15) Statistics of extreme values; tail inference (62G32)
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Uses Software
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