@article {11654,
	title = {Revisiting the maximum likelihood estimation of a positive extreme value index},
	journal = {Journal Of Statistical Theory And PracticeJournal Of Statistical Theory And Practice},
	volume = {9},
	year = {2015},
	note = {<p>Sem PDF.</p>
},
	month = {2015/1/13},
	pages = {200 - 218},
	abstract = {<p>In this article, we revisit Feuerverger and Halls maximum likelihood estimation of the extreme value index. Based on those estimators we propose new estimators that have the smallest possible asymptotic variance, equal to the asymptotic variance of the Hill estimator. The full asymptotic distributional properties of the estimators are derived under a general third-order framework for heavy tails. Applications to a real data set and to simulated data are also presented.In this article, we revisit Feuerverger and Halls maximum likelihood estimation of the extreme value index. Based on those estimators we propose new estimators that have the smallest possible asymptotic variance, equal to the asymptotic variance of the Hill estimator. The full asymptotic distributional properties of the estimators are derived under a general third-order framework for heavy tails. Applications to a real data set and to simulated data are also presented.</p>
},
	keywords = {bias estimation, heavy tails, Semiparametric estimation, Statistics of extremes},
	isbn = {1559-8608},
	url = {http://www.scopus.com/inward/record.url?scp=84909966167\&partnerID=8YFLogxK},
	author = {Caeiro, Frederico and Gomes, M. Ivette}
}
