A sequential design for extreme quantiles estimation under binary sampling. - Laboratoire de Probabilités, Statistique et Modélisation Accéder directement au contenu
Pré-Publication, Document De Travail Année : 2019

A sequential design for extreme quantiles estimation under binary sampling.

Plan d'expérience séquentiel pour l'estimation de quantile extrême sous échantillonnage dichotomique

Résumé

We propose a sequential design method aiming at the estimation of an extreme quantile based on a sample of dichotomic data corresponding to peaks over a given threshold. This study is motivated by an industrial challenge in material reliability and consists in estimating a failure quantile from trials whose outcomes are reduced to indicators of whether the specimen have failed at the tested stress levels. The solution proposed is a sequential design making use of a splitting approach, decomposing the target probability level into a product of probabilities of conditional events of higher order. The method consists in gradually targeting the tail of the distribution and sampling under truncated distributions. The model is GEV, and sequential estimation of its parameters involves an improved maximum likelihood procedure for binary data, due to the large uncertainty associated with such a restricted information.
Fichier principal
Vignette du fichier
2019-07-20-ArticleSplitting.pdf (1 Mo) Télécharger le fichier
Origine : Fichiers éditeurs autorisés sur une archive ouverte

Dates et versions

hal-02190810 , version 1 (19-01-2023)

Licence

Paternité

Identifiants

Citer

Michel Broniatowski, Emilie Miranda. A sequential design for extreme quantiles estimation under binary sampling.. 2019. ⟨hal-02190810⟩
11 Consultations
14 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More