@article {11650,
	title = {A new partially reduced-bias mean-of-order p class of extreme value index estimators},
	journal = {Computational Statistics \& Data AnalysisComputational Statistics \& Data Analysis},
	volume = {82},
	year = {2015},
	note = {<p>Sem PDF.National Funds through FCT-Fundacao para a Ciencia e a Tecnologia (PEst-OE/MAT/UI0006/2014; PEst-OE/MAT/UIO297/2014)</p>
},
	month = {2015},
	pages = {223 - 227},
	abstract = {<p>A class of partially reduced-bias estimators of a positive extreme value index (EVI), related to a mean-of-order-p class of EVI-estimators, is introduced and studied both asymptotically and for finite samples through a Monte-Carlo simulation study. A comparison between this class and a representative class of minimum-variance reduced-bias (MVRB) EVI-estimators is further considered. The MVRB EVI-estimators are related to a direct removal of the dominant component of the bias of a classical estimator of a positive EVI, the Hill estimator, attaining as well minimal asymptotic variance. Heuristic choices for the tuning parameters p and k, the number of top order statistics used in the estimation, are put forward, and applied to simulated and real data.A class of partially reduced-bias estimators of a positive extreme value index (EVI), related to a mean-of-order-p class of EVI-estimators, is introduced and studied both asymptotically and for finite samples through a Monte-Carlo simulation study. A comparison between this class and a representative class of minimum-variance reduced-bias (MVRB) EVI-estimators is further considered. The MVRB EVI-estimators are related to a direct removal of the dominant component of the bias of a classical estimator of a positive EVI, the Hill estimator, attaining as well minimal asymptotic variance. Heuristic choices for the tuning parameters p and k, the number of top order statistics used in the estimation, are put forward, and applied to simulated and real data.</p>
},
	keywords = {bias estimation, Heavy right-tails, Heuristic methods, Optimal levels, semi-parametric estimation, Statistics of extremes},
	isbn = {0167-9473},
	url = {http://www.scopus.com/inward/record.url?scp=84907899862\&partnerID=8YFLogxK},
	author = {Gomes, M. Ivette and Brilhante,M. F{\'a}tima and Caeiro, Frederico and Pestana, Dinis}
}
