Dependence modelling for spatial extremes

By Jennifer L. Wadsworth, Jonathan A. Tawn. 2012

199 citations recorded by the source corpus.

Subfields: Demography, Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/a6f036d9f69f9957610bc476b6c5a4fd5cc040a2

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Citations in the corpus

Geostatistics of Dependent and Asymptotically Independent Extremes (2013, methodology): “For space-time data, hybrid models (Wadsworth and Tawn 2012) can capture different asymptotic properties at different distances and time lags, but they may be quite difficult to fit in practice.”
Statistical Modeling of Spatial Extremes (2012, methodology): “Wadsworth and Tawn (2012) tackle this important topic.”
Space–time modelling of extreme events (2012, background): “Wadsworth and Tawn (2012) have proposed models that can handle both asymptotic independence and asymptotic dependence, and it seems entirely feasible to extend our approach to them.”
INLA goes extreme: Bayesian tail regression for the estimation of high spatio-temporal quantiles (2018, background): “…well-suited to properly 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,…”
Modeling asymptotically independent spatial extremes based on Laplace random fields (2015, methodology): “Useful models pertaining to this framework are obtained by inverting max-stable processes (Wadsworth and Tawn, 2012), allowing for composite likelihood inference.”
Bridging asymptotic independence and dependence in spatial extremes using Gaussian scale mixtures (2016, background): “Al-ternatively, Wadsworth and Tawn (2012) proposed inverted max-stable models, which were found to be slightly more ﬂexible than Gaussian processes in some applications (Thibaud et al., 2013; Davison et al., 2013), but are as diﬃcult to ﬁt as max-stable models.”
Non-Stationary Dependence Structures for Spatial Extremes (2014, methodology): “One possibility would be to “invert” the non-stationary max-stable models proposed above (see Wadsworth and Tawn, 2012; Davison et al., 2013).”
Modeling Spatial Processes with Unknown Extremal Dependence Class (2017, methodology): “Then the process W (s) = 1/Gs{M(s)} has an inverted max-stable copula (Ledford and Tawn, 1996; Wadsworth and Tawn, 2012), Pareto margins, and coefficient of tail dependence ηW (h) = 1/θ(h).”
Likelihood estimators for multivariate extremes (2014, background): “Alternatively, a partially censored pairwise likelihood was proposed by Wadsworth and Tawn (2012).”
Threshold modeling of extreme spatial rainfall (2013, methodology): “In the threshold approach, if the threshold is chosen too low, the dependence structure may not have converged to the max-stable limit.”
Evaluating environmental joint extremes for the offshore industry (2012, background): “Furthermore, Wadsworth and Tawn (2012) propose the adoption of inverted multivariate extreme value distributions with which to admit hybrid extremal dependence structures within the framework of max-stable processes.”