A class of unbiased location invariant Hill-type estimators for heavy tailed distributions

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Based on the methods provided in Caeiro and Gomes (2002) and Fraga Alves (2001), a new class of location invariant Hill-type estimators is derived in this paper. Its asymptotic distributional representation and asymptotic normality are presented, and the optimal choice of sample fraction by Mean Squared Error is also discussed for some special cases. Finally comparison studies are provided for some familiar models by Monte Carlo simulations.
Published in at http://dx.doi.org/10.1214/08-EJS276 the Electronic Journal of Statistics (http://www.i-journals.org/ejs/) by the Institute of Mathematical Statistics (http://www.imstat.org)

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Statistics Theory, 62G32 (Primary) 65C05 (Secondary)

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http://salesiana.dossiersoluciones.com/handle/123456789/169751

Consulte el texto completo en el siguiente enlace:

https://arxiv.org/abs/0809.3869
 http://arxiv.org/abs/0809.3869
 Electronic Journal of Statistics 2008, Vol. 2, 829-847
 doi:10.1214/08-EJS276

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arXiv