On the Hill estimator: a comparison of methods
| Data(s) |
01/10/2015
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| Resumo |
Extreme value theory (EVT) deals with the occurrence of extreme phenomena. The tail index is a very important parameter appearing in the estimation of the probability of rare events. Under a semiparametric framework, inference requires the choice of a number k of upper order statistics to be considered. This is the crux of the matter and there is no definite formula to do it, since a small k leads to high variance and large values of k tend to increase the bias. Several methodologies have emerged in literature, specially concerning the most popular Hill estimator (Hill, 1975). In this work we compare through simulation well-known procedures presented in Drees and Kaufmann (1998), Matthys and Beirlant (2000), Beirlant et al. (2002) and de Sousa and Michailidis (2004), with a heuristic scheme considered in Frahm et al. (2005) within the estimation of a different tail measure but with a similar context. We will see that the new method may be an interesting alternative. Fundação para a Ciência e Tecnologia (FCT): CEMAT (UID/MULTI/04621/2013) |
| Identificador | |
| Idioma(s) |
eng |
| Relação |
Fundação para a Ciência e Tecnologia (FCT): CEMAT (UID/MULTI/04621/2013) |
| Direitos |
info:eu-repo/semantics/openAccess |
| Palavras-Chave | #Extreme value theory #Tail index estimation Monte-Carlo simulations |
| Tipo |
info:eu-repo/semantics/conferenceObject |