La méthode POT (pics au-delà d'un seuil) consiste à utiliser une distribution de Pareto généralisée (GPD) pour approximer la loi des excès au-delà d'un seuil. Dans cette Note, nous proposons des estimateurs de quantiles extrêmes basés sur cette méthode. Nous établissons leurs normalités asymptotiques sous des hypothèses générales.
The POT (Peaks-Over-Threshold) approach consists in using the generalized Pareto distribution (GPD) to approximate the distribution of excesses over thresholds. In this Note, we propose extreme quantile estimators based on this method. We establish their asymptotic normality under suitable general assumptions.
@article{CRMATH_2005__341_5_307_0, author = {Jean Diebolt and Armelle Guillou and Pierre Ribereau}, title = {Asymptotic normality of the extreme quantile estimator based on the {POT} method}, journal = {Comptes Rendus. Math\'ematique}, pages = {307--312}, publisher = {Elsevier}, volume = {341}, number = {5}, year = {2005}, doi = {10.1016/j.crma.2005.06.032}, language = {en}, }
TY - JOUR AU - Jean Diebolt AU - Armelle Guillou AU - Pierre Ribereau TI - Asymptotic normality of the extreme quantile estimator based on the POT method JO - Comptes Rendus. Mathématique PY - 2005 SP - 307 EP - 312 VL - 341 IS - 5 PB - Elsevier DO - 10.1016/j.crma.2005.06.032 LA - en ID - CRMATH_2005__341_5_307_0 ER -
Jean Diebolt; Armelle Guillou; Pierre Ribereau. Asymptotic normality of the extreme quantile estimator based on the POT method. Comptes Rendus. Mathématique, Volume 341 (2005) no. 5, pp. 307-312. doi : 10.1016/j.crma.2005.06.032. https://comptes-rendus.academie-sciences.fr/mathematique/articles/10.1016/j.crma.2005.06.032/
[1] On the estimation of high quantiles, J. Statist. Plann. Inference, Volume 35 (1993), pp. 1-13
[2] Generalized regular variation of second order, J. Austral. Math. Soc. Ser. A, Volume 61 (1996), pp. 381-395
[3] J. Diebolt, A. Guillou, P. Ribereau, Asymptotic normality of extreme quantile estimators based on the peaks-over-threshold approach, submitted for publication, 2005
[4] On smooth statistical tail functionals, Scand. J. Statist., Volume 25 (1998) no. 1, pp. 187-210
[5] On maximum likelihood estimation of the extreme value index, Ann. Appl. Probab., Volume 14 (2004) no. 3, pp. 1179-1201
[6] Sur la distribution limite du terme maximum d'une série aléatoire, Ann. Math., Volume 44 (1943), pp. 423-453
[7] Statistical inference using extreme order statistics, Ann. Statist., Volume 3 (1975), pp. 119-131
Cité par Sources :
Commentaires - Politique
Approximation of the distribution of excesses using a generalized probability weighted moment method
Jean Diebolt; Armelle Guillou; Imen Rached
C. R. Math (2005)
Extreme quantiles estimation for actuarial applications
Emmanuel Delafosse; Armelle Guillou
C. R. Math (2004)
Asymptotic normality of the ET method – application to the ET test
Jean Diebolt; Myriam Garrido; Stéphane Girard
C. R. Math (2003)