@inbook {11656,
	title = {Adaptive estimation of a tail shape second order parameter},
	booktitle = {International Conference of Computational Methods in Sciences and Engineering 2015 (ICCMSE 2015)},
	series = {AIP Conference Proceedings},
	year = {2015},
	note = {<p>Sem PDF.This work was partially supported by the Funda{\c c}{\~a}o para a Ci{\^e}ncia e a Tecnologia (Portuguese Foundation for Science and Technology) through the project UID/MAT/00297/2013 (Centro de Matem{\'a}tica e Aplica{\c c}{\~o}es).</p>
},
	month = {2015/12/31},
	publisher = {American Institute of Physics Inc.},
	organization = {American Institute of Physics Inc.},
	abstract = {<p>In Statistics of Extremes, the tail shape second order parameter is a relevant parameter whenever we want to improve the estimation of first order parameters. We shall consider two semi-parametric estimators of the shape second order parameter, parameterized with a tuning parameter. We provide a Monte Carlo comparative simulation study of several algorithms for the choice of such tuning parameter and for an adaptive estimation of the shape second order parameter.In Statistics of Extremes, the tail shape second order parameter is a relevant parameter whenever we want to improve the estimation of first order parameters. We shall consider two semi-parametric estimators of the shape second order parameter, parameterized with a tuning parameter. We provide a Monte Carlo comparative simulation study of several algorithms for the choice of such tuning parameter and for an adaptive estimation of the shape second order parameter.</p>
},
	keywords = {Asymptotic properties, Heavy tail, Monte Carlo simulation, Shape second-order parameter, Statistics of extremes},
	isbn = {978-073541349-8},
	url = {http://www.scopus.com/inward/record.url?scp=84984535413\&partnerID=8YFLogxK},
	author = {Caeiro, Frederico and Gomes,Dora Susana Raposo Prata}
}
