Semiparametric estimation of the extremal index using block maxima.
Department of Statistical Science, University College London
The extremal index θ , a measure of the degree of local dependence in the extremes of a stationary process, plays an important role in extreme value analyses. We estimate θ semiparametrically, using the relationship between the distribution of block maxima and the marginal distribution of a process to define a semiparametric model. We show that these semiparametric estimators are simpler and substantially more effi cient than their parametric counterparts. We seek to improve e fficiency further using maxima over sliding blocks. An application to sea-surge heights combines inferences about θ with a standard extreme value analysis of block maxima to estimate marginal quantiles.
|Title:||Semiparametric estimation of the extremal index using block maxima|
|Keywords:||Extremal index, semiparametric estimation, extreme value theory, block maxima, sea-surge heights|
|UCL classification:||UCL > School of BEAMS > Faculty of Maths and Physical Sciences > Statistical Science|
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