Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10327539 | Computational Statistics & Data Analysis | 2013 | 18 Pages |
Abstract
The classical Hill estimator of a positive extreme value index (EVI) can be regarded as the logarithm of the geometric mean, or equivalently the logarithm of the mean of order p=0, of a set of adequate statistics. A simple generalisation of the Hill estimator is now proposed, considering a more general mean of order pâ¥0 of the same statistics. Apart from the derivation of the asymptotic behaviour of this new class of EVI-estimators, an asymptotic comparison, at optimal levels, of the members of such class and other known EVI-estimators is undertaken. An algorithm for an adaptive estimation of the tuning parameters under play is also provided. A large-scale simulation study and an application to simulated and real data are developed.
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
M. Fátima Brilhante, M. Ivette Gomes, Dinis Pestana,