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Local asymptotic normality in a stationary model for spatial extremes

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  • Falk, Michael

Abstract

De Haan and Pereira (2006) [6] provided models for spatial extremes in the case of stationarity, which depend on just one parameter [beta]>0 measuring tail dependence, and they proposed different estimators for this parameter. We supplement this framework by establishing local asymptotic normality (LAN) of a corresponding point process of exceedances above a high multivariate threshold. Standard arguments from LAN theory then provide the asymptotic minimum variance within the class of regular estimators of [beta]. It turns out that the relative frequency of exceedances is a regular estimator sequence with asymptotic minimum variance, if the underlying observations follow a multivariate extreme value distribution or a multivariate generalized Pareto distribution.

Suggested Citation

  • Falk, Michael, 2011. "Local asymptotic normality in a stationary model for spatial extremes," Journal of Multivariate Analysis, Elsevier, vol. 102(1), pages 48-60, January.
    • Handle: RePEc:eee:jmvana:v:102:y:2011:i:1:p:48-60
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    References listed on IDEAS

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    1. Deheuvels, Paul, 1983. "Point processes and multivariate extreme values," Journal of Multivariate Analysis, Elsevier, vol. 13(2), pages 257-272, June.
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