TY  - JOUR
ID  - Bouhadjera2022
LB  - Bouhadjera2022
AU  - Bouhadjera, Feriel
AU  - Saïd, Elias Ould
TI  - Strong consistency of the local linear relative regression estimator for censored data
ST  - Strong consistency of the local linear relative regression estimator for censored data
JO  - Opuscula Math.
JA  - Opuscula Math.
JF  - Opuscula Mathematica
PY  - 2022
VL  - 42
IS  - 6
SP  - 805
EP  - 832
DO  - https://doi.org/10.7494/OpMath.2022.42.6.805
UR  - https://doi.org/10.7494/OpMath.2022.42.6.805
AB  - In this paper, we combine the local linear approach to the relative error regression estimation method to build a new estimator of the regression operator when the response variable is subject to random right censoring. We establish the uniform almost sure consistency with rate over a compact set of the proposed estimator. Numerical studies, firstly on simulated data, then on a real data set concerning the death times of kidney transplant patients, were conducted. These practical studies clearly show the superiority of the new estimator compared to competitive estimators.
KW  - censored data
KW  - local linear approach
KW  - relative error
KW  - regression function
KW  - uniform almost sure convergence
SN  - 1232-9274
ER  -