A Sliding Blocks Estimator for the Extremal Index

dc.creatorRobert, Christian Y.
dc.creatorSegers, Johan
dc.creatorFerro, Christopher A. T.
dc.date2008-12-22
dc.date.accessioned2026-07-07T12:21:15Z
dc.date.available2026-07-07T12:21:15Z
dc.descriptionIn extreme value statistics for stationary sequences, blocks estimators are usually constructed by using disjoint blocks because exceedances over high thresholds of different blocks can be assumed asymptotically independent. In this paper we focus on the estimation of the extremal index which measures the degree of clustering of extremes. We consider disjoint and sliding blocks estimators and compare their asymptotic properties. In particular we show that the sliding blocks estimator is more efficient than the disjoint version and has a smaller asymptotic bias. Moreover we propose a method to reduce its bias when considering sufficiently large block sizes.
dc.descriptionSubmitted to the Electronic Journal of Statistics (http://www.i-journals.org/ejs/) by the Institute of Mathematical Statistics (http://www.imstat.org)
dc.identifierhttps://arxiv.org/abs/0812.4233
dc.identifierhttp://arxiv.org/abs/0812.4233
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/213307
dc.subjectStatistics Theory
dc.subject60G70, 62E20 (Primary) 62G20, 62G32 (Secondary)
dc.titleA Sliding Blocks Estimator for the Extremal Index
dc.typetext

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