Extremal Index Estimation for a Weakly Dependent Stationary Sequence

Tailen Hsing

103 citations0/0 files storedThe Annals of Statistics

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Probability and Risk Models Probability and Statistical Research Statistical Methods and Inference

Abstract

Under stationarity and weak dependence, the statistical significance and the estimation of the extremal index are considered. It is shown that the distribution of the sample maximum can be uniformly approximated given the extremal index and the marginal distribution as the sample size increases. An adaptive procedure is proposed for estimating the extremal index. The procedure is shown to be asymptotically optimal in a class of estimators.

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2010ON TAIL INDEX ESTIMATION FOR DEPENDENT, HETEROGENEOUS DATA 2000A Comparison of Methods for Estimating the Extremal Index 1998On blocks and runs estimators of the extremal index 2009Inference for the limiting cluster size distribution of extreme values 2009A sliding blocks estimator for the extremal index 2003New Estimators for the Extremal Index and Other Cluster Characteristics 1998On the distribution of tail array sums for strongly mixing stationary sequences 2007Asymptotically (in)dependent multivariate maxima of moving maxima processes

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