caa a22 4500 467922756 CHVBK 20180406152921.0 cr unu---uuuuu 170328e20061201xx s 000 0 eng 10.1007/s00477-006-0047-4 doi (NATIONALLICENCE)springer-10.1007/s00477-006-0047-4 Statistical analysis of extreme events in a non-stationary context via a Bayesian framework: case study with peak-over-threshold data [Elektronische Daten] [Benjamin Renard, Michel Lang, Philippe Bois] Statistical analysis of extremes currently assumes that data arise from a stationary process, although such an hypothesis is not easily assessable and should therefore be considered as an uncertainty. The aim of this paper is to describe a Bayesian framework for this purpose, considering several probabilistic models (stationary, step-change and linear trend models) and four extreme values distributions (exponential, generalized Pareto, Gumbel and GEV). Prior distributions are specified by using regional prior knowledge about quantiles. Posterior distributions are used to estimate parameters, quantify the probability of models and derive a realistic frequency analysis, which takes into account estimation, distribution and stationarity uncertainties. MCMC methods are needed for this purpose, and are described in the article. Finally, an application to a POT discharge series is presented, with an analysis of both occurrence process and peak distribution. Springer-Verlag, 2006 Bayesian analysis nationallicence Extreme events nationallicence Stationarity nationallicence Uncertainties nationallicence Climate change nationallicence Frequency analysis nationallicence Renard Benjamin U.R. Hydrologie-Hydraulique, Cemagref Centre de Lyon, 3 bis Quai Chauveau, CP 220, 69336, Lyon cedex 09, France aut Lang Michel U.R. Hydrologie-Hydraulique, Cemagref Centre de Lyon, 3 bis Quai Chauveau, CP 220, 69336, Lyon cedex 09, France aut Bois Philippe LTHE, Laboratoire d'études des Transferts en Hydrologie et Environnement, BP53, 38041, Grenoble cedex 09, France aut Stochastic Environmental Research and Risk Assessment Springer-Verlag 21/2(2006-12-01), 97-112 1436-3240 21:2<97 2006 21 477 https://doi.org/10.1007/s00477-006-0047-4 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s00477-006-0047-4 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Renard Benjamin U.R. Hydrologie-Hydraulique, Cemagref Centre de Lyon, 3 bis Quai Chauveau, CP 220, 69336, Lyon cedex 09, France aut NATIONALLICENCE 700 1- Lang Michel U.R. Hydrologie-Hydraulique, Cemagref Centre de Lyon, 3 bis Quai Chauveau, CP 220, 69336, Lyon cedex 09, France aut NATIONALLICENCE 700 1- Bois Philippe LTHE, Laboratoire d'études des Transferts en Hydrologie et Environnement, BP53, 38041, Grenoble cedex 09, France aut NATIONALLICENCE 773 0- Stochastic Environmental Research and Risk Assessment Springer-Verlag 21/2(2006-12-01), 97-112 1436-3240 21:2<97 2006 21 477 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer