@article {1200.62052,
	title = {Semi-parametric tail inference through probability-weighted moments.},
	journal = {J. Stat. Plann. Inference},
	volume = {141},
	number = {2},
	year = {2011},
	note = {<p>n/a</p>
},
	pages = {937-950},
	abstract = {<p>{Summary: For heavy-tailed models, and working with the sample of the $k$ largest observations, we present probability weighted moments (PWM) estimators for the first order tail parameters. Under regular variation conditions on the right-tail of the underlying distribution function $F$ we prove the consistency and asymptotic normality of these estimators. Their performance, for finite sample sizes, is illustrated through a small-scale Monte Carlo simulation.}</p>
},
	keywords = {extreme value index, first order scale parameter, semi-parametric estimation, statistics of extremes}, {heavy tails},
	doi = {10.1016/j.jspi.2010.08.015},
	author = {Caeiro, Frederico and Gomes, M.Ivette}
}
