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Numerical convergence of the Block-Maxima approach to the generalized extreme value distribution

Faranda, D., Lucarini, V., Turchetti, G. and Vaienti, S. (2011) Numerical convergence of the Block-Maxima approach to the generalized extreme value distribution. Journal of Statistical Physics, 145 (5). pp. 1156-1180. ISSN 0022-4715

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To link to this article DOI: 10.1007/s10955-011-0234-7

Abstract/Summary

In this paper we perform an analytical and numerical study of Extreme Value distributions in discrete dynamical systems. In this setting, recent works have shown how to get a statistics of extremes in agreement with the classical Extreme Value Theory. We pursue these investigations by giving analytical expressions of Extreme Value distribution parameters for maps that have an absolutely continuous invariant measure. We compare these analytical results with numerical experiments in which we study the convergence to limiting distributions using the so called block-maxima approach, pointing out in which cases we obtain robust estimation of parameters. In regular maps for which mixing properties do not hold, we show that the fitting procedure to the classical Extreme Value Distribution fails, as expected. However, we obtain an empirical distribution that can be explained starting from a different observable function for which Nicolis et al. (Phys. Rev. Lett. 97(21): 210602, 2006) have found analytical results.

Item Type:Article
Refereed:Yes
Divisions:Interdisciplinary centres and themes > Walker Institute for Climate System Research
Faculty of Science > School of Mathematical and Physical Sciences > Department of Mathematics and Statistics
ID Code:27141
Publisher:Springer

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