Title :

Robust regression analysis for a censored response and functional regressors

Author(s) :

Hennani, L. Ait [Auteur]
Lemdani, Mohamed [Auteur]
Laboratoire de Biomathématiques
Said, Elias Ould [Auteur]

Journal title :

Journal of nonparametric statistics

Abbreviated title :

J. Nonparametr. Stat.

Volume number :

31

Pages :

221-243

Publisher :

Taylor & Francis

Publication date :

2019-01-01

ISSN :

1048-5252

English keyword(s) :

robust estimation
kernel estimator
Asymptotic normality
functional random variable
censored data

HAL domain(s) :

Sciences du Vivant [q-bio]

English abstract : [en]

Let (Tn)n≥1 be an independent and identically distributed (iid) sequence of interest random variables (rv) distributed as T. In censorship models, T is subject to random censoring by another rv C. Based on the so-called ...
Show more >Let (Tn)n≥1 be an independent and identically distributed (iid) sequence of interest random variables (rv) distributed as T. In censorship models, T is subject to random censoring by another rv C. Based on the so-called synthetic data, we define an M-estimator for the regression function of T given a functional covariate χ. Under standard assumptions on the kernel, bandwidth and small ball probabilities, we establish its strong consistency with rate and asymptotic normality. The asymptotic variance is given explicitly. Confidence bands are given and special cases are studied to show the generality of our work. Finally simulations are drawn to illustrate both quality of fit and robustness.Show less >

Language :

Anglais

Audience :

Internationale

Popular science :

Non

Administrative institution(s) :

CHU Lille
Université de Lille

Collections :

• METRICS : Evaluation des technologies de santé et des pratiques médicales - ULR 2694

Submission date :

2019-12-09T18:20:38Z
2024-04-10T09:09:18Z