An extreme quantile estimator for the log-generalized Weibull-tail model

Abstract : A new estimator for extreme quantiles is proposed under the log-generalized Weibull-tail model, ntroduced by (de Valk, C., Extremes, pp. 661--686, vol. 19, 2016). This model relies on a new regular variation condition which, in some situations, permits to extrapolate further into the tails than the classical assumption in extreme-value theory. The asymptotic normality of the estimator is established and its finite sample properties are illustrated both on simulated and real datasets.
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Submitted on : Wednesday, January 23, 2019 - 3:41:35 PM
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Clément Albert, Anne Dutfoy, Laurent Gardes, Stéphane Girard. An extreme quantile estimator for the log-generalized Weibull-tail model. Econometrics and Statistics , Elsevier, In press, pp.1-39. ⟨10.1016/j.ecosta.2019.01.004⟩. ⟨hal-01783929v4⟩

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