Modeling Extreme Events: Sample Fraction Adaptive Choice in Parameter Estimation

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2012

Autores

Manuela Neves (Autor) Outra; Ivette Gomes (Autor) Outra; Fernanda Figueiredo (Autor) FEP; Dora Prata Gomes (Autor) Outra

Ata de Conferência Internacional

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

Páginas: 1110-1113

International Conference of Numerical Analysis and Applied Mathematics (ICNAAM)

Kos, GREECE, SEP 19-25, 2012

Indexação

ISI Proceedings

ISI Web of Knowledge - 1 Citação

Scopus - 1 Citação

Classificação Científica

FOS: Ciências exactas e naturais

Outras Informações

ID Authenticus: 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.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 4