Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/55225

TitleAnalysis of estimation methods for the extremal index
Author(s)Ferreira, Marta Susana
KeywordsDeclustering
Extreme value theory
Local dependence conditions
Stationary sequences
Issue dateApr-2018
PublisherUniversità del Salento
JournalElectronic Journal of Applied Statistical Analysis
Abstract(s)Many datasets present time-dependent variation and short-term clustering within extreme values. The extremal index is a primary measure to evaluate clustering of high values in a stationary sequence. Estimation procedures are based on the choice of a threshold and/or a declustering parameter or a block size. Here we revise several different methods and compare them through simulation. In particular, we will see that a recent declustering methodology may be useful for the popular runs estimator and for a new estimator that works under the validation of a local dependence condition. An application to real data is also presented.
TypeArticle
URIhttp://hdl.handle.net/1822/55225
DOI10.1285/i20705948v11n1p296
ISSN2070-5948
e-ISSN2070-5948
Peer-Reviewedyes
AccessOpen access
Appears in Collections:CMAT - Artigos em revistas com arbitragem / Papers in peer review journals

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