Improving Asymptotically Unbiased Extreme Value Index Estimation View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2018

AUTHORS

Frederico Caeiro , Ivanilda Cabral , M. Ivette Gomes

ABSTRACT

The extreme value index characterizes the tail behaviour of a distribution, and indicates the size and frequency of certain extreme events under a given probability model. In this work, we are interested in improvements attained through the reduction of bias of the extreme value index estimators related to Lehmer’s mean of the log-excesses. A comparison with other reduced bias estimators, namely the corrected-Hill estimator, in Caeiro et al. (Revstat 3(2):111–136, 2005), is also performed. More... »

PAGES

155-163

Book

TITLE

Recent Studies on Risk Analysis and Statistical Modeling

ISBN

978-3-319-76604-1
978-3-319-76605-8

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-76605-8_11

DOI

http://dx.doi.org/10.1007/978-3-319-76605-8_11

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1106289784


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