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B1238
Title: Hierarchical space-time modeling of exceedances Authors:  Gwladys Toulemonde - Université de Montpellier (France) [presenting]
Jean-Noel Bacro - Universite de Montpellier (France)
Carlo Gaetan - University of Venice (Italy)
Thomas Opitz - BioSP, INRA (France)
Abstract: The statistical modeling of space-time extremes in environmental applications is a valuable approach to understand complex dependences in observed data and to generate realistic scenarios for impact models. Motivated by hourly rainfall data in Southern France presenting asymptotic independence, we propose a novel hierarchical model for high threshold exceedances leading to asymptotic independence in space and time. The approach is based on representing a generalized Pareto distribution as a Gamma mixture of an exponential distribution, enabling us to keep marginal distributions which are coherent with univariate extreme value theory. The key idea is to use a kernel convolution of a space-time Gamma random process based on influence zones defined as cylinders with an ellipsoidal basis to generate anisotropic spatio-temporal dependence in exceedances. Statistical inference is based on a composite likelihood for the observed censored excesses. The practical usefulness of our model is illustrated on the previously mentioned hourly precipitation data set from a region in Southern France.