Tail and quantile estimation for real-valued β-mixing spatial data
Résumé
This paper deals with extreme-value index estimation of a heavy-tailed distribution of a spatial dependent process. We are particularlyinterested in spatial rare events of a β−mixing process. Given a sta-tionary real-valued multidimensional spatial process {X_i,i ∈ Z^N}, weinvestigate its heavy-tail index estimation. Asymptotic properties ofthe corresponding estimator are established under mildmixingcondi-tions. The particularity of the tail proposed estimator is based on thespatial nature of the sample and its unbiased and reduced variance prop-erties compared to well known tail index estimators. Extreme quantileestimation is also deduced. A numerical study on synthetic and realdatasets is conducted to assess the finite-sample behaviour of the pro-posed estimators.
Origine | Fichiers produits par l'(les) auteur(s) |
---|