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Construction of generalized Pareto vectors for flexible peaks-over-threshold modeling

Authors :
Toulemonde, Gwladys
Bacro, Jean-Noel
Gaetan, Carlo
Opitz, Thomas
Institut Montpelliérain Alexander Grothendieck (IMAG)
Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)
Littoral, Environment: MOdels and Numerics (LEMON)
Inria Sophia Antipolis - Méditerranée (CRISAM)
Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut Montpelliérain Alexander Grothendieck (IMAG)
Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Hydrosciences Montpellier (HSM)
Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)
Université de Venise Ca’ Foscari | Università Ca’ Foscari di Venezia
Biostatistique et Processus Spatiaux (BioSP)
Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
CFEnetwork
Source :
CMStatistics 2022-15th International Conference of the ERCIM WG on Computational and Methodological Statistics, CMStatistics 2022-15th International Conference of the ERCIM WG on Computational and Methodological Statistics, CFEnetwork, Dec 2022, London, United Kingdom
Publication Year :
2022
Publisher :
HAL CCSD, 2022.

Abstract

International audience; A flexible multivariate threshold exceedances modeling is defined based on componentwise ratios between any two independent random vectors with exponential and Gamma marginal distributions. This construction allows flexibility in terms of extremal bivariate dependence. More precisely, asymptotic dependence and independence are possible, as well as hybrid situations. Two useful parametric model classes will be presented. Oneof the two, based on Gamma convolution models, will be illustrated through a simulation study. Good performance is shown for likelihood-based estimation of summaries of bivariate extremal dependence for several scenarii.

Details

Language :
English
Database :
OpenAIRE
Journal :
CMStatistics 2022-15th International Conference of the ERCIM WG on Computational and Methodological Statistics, CMStatistics 2022-15th International Conference of the ERCIM WG on Computational and Methodological Statistics, CFEnetwork, Dec 2022, London, United Kingdom
Accession number :
edsair.od.......165..7c9359a74d4fb72607bd4b1f8bceb066