Modeling Extreme Events: Sample Fraction Adaptive Choice in Parameter Estimation

• Type: Article in International Conference Proceedings Book
• Date: 2012

Authors

Manuela Neves (Author) Other; Ivette Gomes (Author) Other; Fernanda Figueiredo (Author) FEP; Dora Prata Gomes (Author) Other

Conference proceedings International

Title: NUMERICAL ANALYSIS AND APPLIED MATHEMATICS (ICNAAM 2012), VOLS A AND B

Pages: 1110-1113

International Conference of Numerical Analysis and Applied Mathematics (ICNAAM)

Kos, GREECE, SEP 19-25, 2012

Indexing

ISI Proceedings

ISI Web of Knowledge - 1 Citation

Scopus - 1 Citation

Scientific classification

FOS: Natural sciences

Other information

Authenticus ID: P-002-EXP

DOI: 10.1063/1.4756342

Abstract (EN): When modeling extreme events there are a few primordial parameters, among which we refer the extreme value index and the extremal index. The extreme value index measures the right tail-weight of the underlying distribution and the extremal index characterizes the degree of local dependence in the extremes of a stationary sequence. Most of the semi-parametric estimators of these parameters show the same type of behaviour: nice asymptotic properties, but a high variance for small values of k, the number of upper order statistics to be used in the estimation, and a high bias for large values of k. This shows a real need for the choice of k. Choosing some well-known estimators of those parameters we revisit the application of a heuristic algorithm for the adaptive choice of k. The procedure is applied to some simulated samples as well as to some real data sets.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 4