Approximating the conditional density given large observed values via a multivariate extremes framework, with application to environmental data

DOI10.1214/12-AOAS554zbMath1257.62118arXiv1301.1428OpenAlexW2092172930WikidataQ116752823 ScholiaQ116752823MaRDI QIDQ1939994

Daniel Cooley, Richard A. Davis, Philippe Naveau

Publication date: 5 March 2013

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1301.1428

zbMATH Keywords

air pollutionthreshold exceedancesmultivariate regular variationangular or spectral measurenitrogen dioxide monitoring

Mathematics Subject Classification ID

Multivariate distribution of statistics (62H10) Applications of statistics to environmental and related topics (62P12) Statistics of extreme values; tail inference (62G32)

Related Items

Section on the special year for Mathematics of Planet Earth (MPE 2013) ⋮ Conditional sampling for max-stable processes with a mixed moving maxima representation ⋮ Geostatistics of dependent and asymptotically independent extremes ⋮ Statistical Inference for Max-Stable Processes by Conditioning on Extreme Events ⋮ Forecaster's dilemma: extreme events and forecast evaluation ⋮ Regression-type analysis for multivariate extreme values ⋮ Conditional independence in max-linear Bayesian networks

Uses Software

• ismev
• evd

Cites Work

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