V. Asimit, D. Li, and L. Peng, Pitfalls in using Weibull tailed distributions, Pitfalls in using Weibull tailed distributions, pp.2018-2024, 2010.
DOI : 10.1016/j.jspi.2010.01.039

J. Beirlant, C. Bouquiaux, and B. Werker, Semiparametric lower bounds for tail index estimation, Journal of Statistical Planning and Inference, vol.136, issue.3, pp.705-729, 2006.
DOI : 10.1016/j.jspi.2004.08.018

J. Beirlant, M. Broniatowski, J. L. Teugels, and P. Vynckier, The mean residual life function at great age: Applications to tail estimation, Journal of Statistical Planning and Inference, vol.45, issue.1-2, pp.21-48, 1995.
DOI : 10.1016/0378-3758(94)00061-1

J. Beirlant, G. Dierckx, Y. Goegebeur, and G. Matthys, Tail index estimation and an exponential regression model, pp.177-200, 1999.

J. Beirlant and J. L. Teugels, Modeling large claims in non-life insurance, Insurance: Mathematics and Economics, vol.11, issue.1, pp.17-29, 1992.
DOI : 10.1016/0167-6687(92)90085-P

M. Berred, Record values and the estimation of the Weibull tail-coefficient, Comptes Rendus de l'Académie des Sciences, T. 312, Série I, pp.943-946, 1991.

M. Broniatowski, On the estimation of the Weibull tail coefficient, Journal of Statistical Planning and Inference, vol.35, issue.3, pp.349-366, 1993.
DOI : 10.1016/0378-3758(93)90022-X

J. Diebolt, L. Gardes, S. Girard, and A. Guillou, Bias-reduced estimators of the Weibull tail-coefficient, TEST, vol.34, issue.3, pp.311-331, 2008.
DOI : 10.1007/s11749-006-0034-6
URL : https://hal.archives-ouvertes.fr/hal-00008881

J. Diebolt, L. Gardes, S. Girard, and A. Guillou, Bias-reduced extreme quantile estimators of Weibull tail-distributions, Journal of Statistical Planning and Inference, vol.138, issue.5, pp.1389-1401, 2008.
DOI : 10.1016/j.jspi.2007.04.025

G. Dierckx, J. Beirlant, D. De-waal, and A. Guillou, A new estimation method for Weibull-type tails based on the mean excess function, Journal of Statistical Planning and Inference, vol.139, issue.6, 1905.
DOI : 10.1016/j.jspi.2008.08.024

O. Ditlevsen, Distribution Arbitrariness in Structural Reliability, Structural Safety and Reliability, pp.1241-1247, 1994.

G. Draisma, L. De-haan, L. Peng, and T. T. Peireira, A Bootstrap-based method to achieve optimality in estimating the extreme-value index, Extremes, pp.367-404, 1999.

M. Falk, Some Best Parameter Estimates for Distributions with Finite Endpoint, Statistics, vol.18, issue.1-2, pp.115-125, 1995.
DOI : 10.1080/02331889508802515

A. Feuerverger and P. Hall, Estimating a tail exponent by modelling departure from a Pareto distribution, Annals of Statistics, vol.27, pp.760-781, 1999.

F. Alves, M. I. De-haan, L. Neves, and C. , A test procedure for detecting super-heavy tails, Journal of Statistical Planning and Inference, vol.139, issue.2, pp.213-227, 2009.
DOI : 10.1016/j.jspi.2008.04.026

J. Galambos, THE ASYMPTOTIC THEORY OF EXTREME ORDER STATISTICS, 1987.
DOI : 10.1016/B978-0-12-702101-0.50014-7

L. Gardes and S. Girard, Estimating extreme quantiles of Weibull tail-distributions, Communication in Statistics -Theory and Methods, pp.1065-1080, 2005.

L. Gardes and S. Girard, Comparison of Weibull tail-coefficient estimators, REVSTAT -Statistical Journal, vol.4, pp.163-188, 2006.
URL : https://hal.archives-ouvertes.fr/hal-00103260

L. Gardes and S. Girard, Estimation of the Weibull tail-coefficient with linear combination of upper order statistics, Journal of Statistical Planning and Inference, vol.138, issue.5, pp.1416-1427, 2008.
DOI : 10.1016/j.jspi.2007.04.026
URL : https://hal.archives-ouvertes.fr/hal-00009161

J. L. Geluk and L. De-haan, Regular Variation, Extensions and Tauberian Theorems, Math Centre Tracts, vol.40, 1987.

S. Girard, A Hill type estimate of the Weibull tail-coefficient, Communication in Statistics -Theory and Methods, pp.205-234, 2004.

Y. Goegebeur, J. Beirlant, and T. De-wet, Generalized kernel estimators for the Weibull-tail coefficient, Communications in Statistics -Theory and Methods, to appear, 2010.

Y. Goegebeur and A. Guillou, Goodness-of-fit testing for Weibull-type behavior, Journal of Statistical Planning and Inference, vol.140, issue.6, pp.1417-1436, 2010.
DOI : 10.1016/j.jspi.2009.12.008

I. Gomes and F. Caeiro, A class of asymptotically unbiased semi-parametric estimators of the tail index, Test, vol.11, issue.2, pp.345-364, 2002.

I. Gomes, F. Caeiro, and F. Figueiredo, Bias reduction of a tail index estimator through an external estimation of the second-order parameter, Statistics, vol.44, issue.6, pp.38-497, 2004.
DOI : 10.1016/S0167-7152(97)00160-0

L. De-haan and A. Ferreira, Extreme Value Theory: An Introduction, Series in Operations Research and Financial Engineering, 2006.
DOI : 10.1007/0-387-34471-3

L. De-haan and L. Peng, Comparison of tail index estimators, Statistica Neerlandica, vol.52, issue.1, pp.60-70, 1998.
DOI : 10.1111/1467-9574.00068

R. J. Harris, Gumbel re-visited - a new look at extreme value statistics applied to wind speeds, Journal of Wind Engineering and Industrial Aerodynamics, vol.59, issue.1, pp.1-22, 1996.
DOI : 10.1016/0167-6105(95)00029-1

E. Häusler and J. L. Teugels, On asymptotic normality of Hill's estimator for the exponent of regular variation, The Annals of Statistics, pp.743-756, 1985.

B. M. Hill, A simple general approach to inference about the tail of a distribution, The Annals of Statistics, pp.1163-1174, 1975.

V. V. Petrov, Sums of independent random variables, 1975.
DOI : 10.1007/978-3-642-65809-9

J. Smith, Estimating the upper tail of flood frequency distributions, Water Resources Research, vol.18, issue.4, pp.1657-1666, 1991.
DOI : 10.1029/WR023i008p01657

I. Weissman, Estimation of parameters and large quantiles based on the k largest observations, Journal of the American Statistical Association, vol.73, pp.812-815, 1978.