CLT for single functional index quantile regression under dependence structure

In this paper, we investigate the asymptotic properties of a nonparametric conditional quantile estimation in the single functional index model for dependent functional data and censored at random responses are observed. First of all, we establish asymptotic properties for a conditional distribution...

Full description

Bibliographic Details
Main Authors: Kadiri Nadia, Rabhi Abbes, Khardani Salah, Akkal Fatima
Format: Article
Language:English
Published: Sciendo 2021-08-01
Series:Acta Universitatis Sapientiae: Mathematica
Subjects:
Online Access:https://doi.org/10.2478/ausm-2021-0003
Description
Summary:In this paper, we investigate the asymptotic properties of a nonparametric conditional quantile estimation in the single functional index model for dependent functional data and censored at random responses are observed. First of all, we establish asymptotic properties for a conditional distribution estimator from which we derive an central limit theorem (CLT) of the conditional quantile estimator. Simulation study is also presented to illustrate the validity and finite sample performance of the considered estimator. Finally, the estimation of the functional index via the pseudo-maximum likelihood method is discussed, but not tackled.
ISSN:2066-7752