@inbook {11649,
	title = {A log probability weighted moment estimator of extreme quantiles},
	booktitle = {Theory and Practice of Risk Assessment - ICRA5 2013},
	volume = {136},
	year = {2015},
	note = {<p>sem pdf conforme despacho</p>
},
	month = {2015},
	pages = {293 - 303},
	publisher = {Springer New York LLC},
	organization = {Springer New York LLC},
	abstract = {<p>In this paper we consider the semi-parametric estimation of extreme quantiles of a right heavy-tail model. We propose a new Probability Weighted Moment estimator for extreme quantiles, which is obtained from the estimators of the shape and scale parameters of the tail. Under a second-order regular variation condition on the tail, of the underlying distribution function, we deduce the non degenerate asymptotic behaviour of the estimators under study and present an asymptotic comparison at their optimal levels. In addition, the performance of the estimators is illustrated through an application to real data.In this paper we consider the semi-parametric estimation of extreme quantiles of a right heavy-tail model. We propose a new Probability Weighted Moment estimator for extreme quantiles, which is obtained from the estimators of the shape and scale parameters of the tail. Under a second-order regular variation condition on the tail, of the underlying distribution function, we deduce the non degenerate asymptotic behaviour of the estimators under study and present an asymptotic comparison at their optimal levels. In addition, the performance of the estimators is illustrated through an application to real data.</p>
},
	keywords = {Extreme quantile, extreme value index, Log probability weighted moment, Optimal level, Statistics of extremes},
	url = {http://www.scopus.com/inward/record.url?scp=84946404285\&partnerID=8YFLogxK},
	author = {Caeiro, Frederico and Gomes,Dora Susana Raposo Prata}
}
