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Communication Dans Un Congrès Année : 2007

Nonparametric estimation of the conditional tail index

Résumé

We present a nonparametric family of estimators for the tail index of a Pareto-type distribution when covariate information is available. Our estimators are based on a weighted sum of the log-spacings between some selected observations. This selection is achieved through a moving window approach on the covariate domain and a random threshold on the variable of interest. Asymptotic normality is proved under mild regularity conditions and illustrated for some weight functions. Finite sample performances are presented on a real data study.
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Dates et versions

hal-00987250 , version 1 (05-05-2014)

Identifiants

  • HAL Id : hal-00987250 , version 1

Citer

Laurent Gardes, Stéphane Girard. Nonparametric estimation of the conditional tail index. Statistical Extremes and Environmental Risk Workshop, Feb 2007, Lisbonne, Portugal. pp.47-50. ⟨hal-00987250⟩
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