Asymptotic comparison at optimal levels of reduced-bias extreme value index estimators
Version of Record online: 3 JUL 2011
© 2011 The Authors. Statistica Neerlandica © 2011 VVS
Volume 65, Issue 4, pages 462–488, November 2011
How to Cite
Caeiro, F. and Gomes, M. I. (2011), Asymptotic comparison at optimal levels of reduced-bias extreme value index estimators. Statistica Neerlandica, 65: 462–488. doi: 10.1111/j.1467-9574.2011.00495.x
- Issue online: 20 OCT 2011
- Version of Record online: 3 JUL 2011
- Received: September 2010. Revised: March 2011.
- statistics of extremes;
- semi-parametric estimation;
- bias estimation;
- heavy tails;
- optimal levels
In this article we are interested in the asymptotic comparison, at optimal levels, of a set of semi-parametric reduced-bias extreme value (EV) index estimators, valid for a wide class of heavy-tailed models, underlying the available data. Again, as in the classical case, there is not any estimator that can always dominate the alternatives, but interesting clear-cut patterns are found. Consequently, and in practice, a suitable choice of a set of EV index estimators will jointly enable us to better estimate the EV index γ, the primary parameter of extreme events.