Space‒time max-stable models with spectral separability

Author:

Embrechts Paul,Koch Erwan,Robert Christian

Abstract

AbstractNatural disasters may have considerable impact on society as well as on the (re-)insurance industry. Max-stable processes are ideally suited for the modelling of the spatial extent of such extreme events, but it is often assumed that there is no temporal dependence. Only a few papers have introduced spatiotemporal max-stable models, extending the Smith, Schlather and Brown‒Resnick spatial processes. These models suffer from two major drawbacks: time plays a similar role to space and the temporal dynamics are not explicit. In order to overcome these defects, we introduce spatiotemporal max-stable models where we partly decouple the influence of time and space in their spectral representations. We introduce both continuous- and discrete-time versions. We then consider particular Markovian cases with a max-autoregressive representation and discuss their properties. Finally, we briefly propose an inference methodology which is tested through a simulation study.

Publisher

Cambridge University Press (CUP)

Subject

Applied Mathematics,Statistics and Probability

Reference29 articles.

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3. Stationary max-stable processes with the Markov property

4. Bienvenüe A. and Robert C. Y. (2014).Likelihood based inference for high-dimensional extreme value distributions. Preprint. Available at http://arxiv.org/abs/1403.0065v3.

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