Threshold modeling of extreme spatial rainfall

By Emeric Thibaud, Raphaël Mutzner, A. C. Davison. 2013

117 citations recorded by the source corpus.

Subfields: Finance, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/bb11ed592ec1fc99b355fa2ab647b41bbb3a5ca1

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Citations in the corpus

Modeling the spatial dependence of floods using the Fisher copula (2019, methodology): “…their timing within a year (Blanchet et al., 2018) To overcome this, the max-stable framework has been extended to the peak-over-threshold setting (Thibaud et al., 2013) Max-stable models have often been applied in the context of extreme precipitation (see, e.g., Blanchet et al., 2018; Davison et…”
Efficient inference and simulation for elliptical Pareto processes (2013, methodology): “, 2009) have proven to be well-suited for modelling extremal dependence of environmental data (Davison et al., 2012, 2013; Thibaud et al., 2013).”
Factor Copula Models for Replicated Spatial Data (2015, methodology): “We next show that the stable upper tail dependence function (Segers, 2012) of the limiting extreme-value copula in the exponential factor model (Example 2) corresponds to the Hüsler and Reiss (1989) distribution, which has been widely used as a flexible family to model extreme events (Davison et al.”
Bridging asymptotic independence and dependence in spatial extremes using Gaussian scale mixtures (2016, background): “…while the middle and right columns display asymptotic independence. censored approach is now quite popular in statistics of extremes (see, e.g., Thibaud et al., 2013; Huser and Davison, 2014; Wadsworth and Tawn, 2014), and results from Thibaud and Opitz (2015) and Huser et al. (2016) suggest…”
INLA goes extreme: Bayesian tail regression for the estimation of high spatio-temporal quantiles (2018, background): “…capture space-time dependence, and it would be interesting to extend our methodological framework to more complex spatial (Wadsworth and Tawn, 2012; Thibaud et al. , 2013; Thibaud and Opitz, 2015; Huser et al. , 2017; Castro Camilo and Huser, 2017; Huser and Wadsworth, 2018) and spatio-temporal…”
Non-Stationary Dependence Structures for Spatial Extremes (2014, methodology): “y can only be computed for dimension D= 2. This explains why pairwise likelihoods (Lindsay, 1988; Varin et al., 2011) have become the standard tool for inference in this context (Padoan et al., 2010; Thibaud et al., 2013; Huser and Davison, 2014), although more ecient approaches based on the point p”
Modeling asymptotically independent spatial extremes based on Laplace random fields (2015, methodology): “We follow common practice in spatial extreme value modeling and use the empirical distribution below the threshold by assuming dense observations in the bulk region of the distribution (Coles and Tawn, 1991; Wadsworth and Tawn, 2012, 2013).”