Adaptive estimation of heavy right tails: resampling-based methods in action

• Type: Article in International Scientific Journal
• Date: 2012

Authors

gomes, mi (Author) Other; figueiredo, f (Author) FEP; neves, mm (Author) Other

Journal

Title: Extremes

Vol. 15 No. 4

Pages: 463-489

ISSN: 1386-1999

Publisher: Springer Nature

Indexing

ISI Web of Knowledge - 29 Citations

ISI Web of Science

Scopus - 45 Citations

Scientific classification

FOS: Natural sciences > Mathematics

Other information

Authenticus ID: P-002-348

DOI: 10.1007/s10687-011-0146-6

Abstract (EN): In this paper, we discuss an algorithm for the adaptive estimation of a positive extreme value index, gamma, the primary parameter in Statistics of Extremes. Apart from the classical extreme value index estimators, we suggest the consideration of associated second-order corrected-bias estimators, and propose the use of resampling-based computer-intensive methods for an asymptotically consistent choice of the thresholds to use in the adaptive estimation of gamma. The algorithm is described for a classical gamma-estimator and associated corrected-bias estimator, but it can work similarly for the estimation of other parameters of extreme events, like a high quantile, the probability of exceedance or the return period of a high level.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 27