Spline regression for hazard rate estimation when data are censored and measured with error

Abstract : In this paper, we study an estimation problem where the variables of interest are subject to both right censoring and measurement error. In this context, we propose a nonparametric estimation strategy of the hazard rate, based on a regression contrast minimized in a finite dimensional functional space generated by splines bases. We prove a risk bound of the estimator in term of integrated mean square error, discuss the rate of convergence when the dimension of the projection space is adequately chosen. Then, we define a data driven criterion of model selection and prove that the resulting estimator performs an adequate compromise. The method is illustrated via simulation experiments which prove that the strategy is successful.
Type de document :
Article dans une revue
Statistica Neerlandica, Wiley, 2017, 71 (2), pp.115-140. <http://onlinelibrary.wiley.com/doi/10.1111/stan.12103/full>. <10.1111/stan.12103>
Liste complète des métadonnées


https://hal.archives-ouvertes.fr/hal-01300739
Contributeur : Fabienne Comte <>
Soumis le : lundi 11 avril 2016 - 13:51:49
Dernière modification le : mardi 25 avril 2017 - 01:08:47
Document(s) archivé(s) le : mardi 12 juillet 2016 - 11:52:29

Fichier

CensureSpline3.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

Citation

Fabienne Comte, Gwennaelle Mabon, Adeline Samson. Spline regression for hazard rate estimation when data are censored and measured with error. Statistica Neerlandica, Wiley, 2017, 71 (2), pp.115-140. <http://onlinelibrary.wiley.com/doi/10.1111/stan.12103/full>. <10.1111/stan.12103>. <hal-01300739>

Partager

Métriques

Consultations de
la notice

286

Téléchargements du document

62