The K Nearest Neighbors Estimation of the Conditional Hazard Function for Functional Data

Mohammed Kadi Attouch; Fatima Zohra Belabed

doi:10.57805/revstat.v12i3.154

The K Nearest Neighbors Estimation of the Conditional Hazard Function for Functional Data

Authors

Mohammed Kadi Attouch Université Djillali Liabès
Fatima Zohra Belabed Université Djillali Liabès

DOI:

https://doi.org/10.57805/revstat.v12i3.154

Keywords:

functional data, nonparametric regression, k-NN estimator, the conditional hazard function, rate of convergence, random bandwidth, asymptotic normality

Abstract

In this paper, we study the nonparametric estimator of the conditional hazard function using the k nearest neighbors (k-NN) estimation method for a scalar response variable given a random variable taking values in a semi-metric space. We give the almost complete convergence (its corresponding rate) of this estimator and we establish the asymptotic normality. Then the effectiveness of this method is exhibited by a comparison with the kernel method estimation given in Ferraty et al. ([12]) and Laksaci and Mechab ([15]) in both cases simulated data and real data.

Downloads

REVSTAT2014v12n3_4

Published

2014-12-23

How to Cite

Kadi Attouch , M., & Zohra Belabed , F. (2014). The K Nearest Neighbors Estimation of the Conditional Hazard Function for Functional Data. REVSTAT-Statistical Journal, 12(3), 273–297. https://doi.org/10.57805/revstat.v12i3.154