Geodesic
Local linear estimation of the trimmed regression for censored data
Filomat, Tome 36 (2022) no. 14, p. 4919

Voir la notice de l'article provenant de la source eLibrary of Mathematical Institute of the Serbian Academy of Sciences and Arts

DOI

We introduce a non-parametric estimation of the trimmed regression by using the local linear method of a censored scalar response variable, given a functional covariate. The main result of this work is the establishment of almost complete convergence for the constructed estimator. A simulation study is carried out to compare the finite sample performance based on the mean square error between the classic local linear regression estimator and the trimmed local linear regression estimator. Moreover, a real data study is used to illustrate our methodology.
DOI : 10.2298/FIL2214919B
Classification : 62G35, 62R10 62G05, 62G08, 62N01
Keywords: Nonparametric robustness, Functional data analysis, Nonparametric regression, Nonparametric estimation, Robust estimation, Censored data 
Ataouia Bakhtaoui; Faiza Limam-Belarbi. Local linear estimation of the trimmed regression for censored data. Filomat, Tome 36 (2022) no. 14, p. 4919 . doi: 10.2298/FIL2214919B
@article{10_2298_FIL2214919B,
     author = {Ataouia Bakhtaoui and Faiza Limam-Belarbi},
     title = {Local linear estimation of the trimmed regression for censored data},
     journal = {Filomat},
     pages = {4919 },
     year = {2022},
     volume = {36},
     number = {14},
     doi = {10.2298/FIL2214919B},
     language = {en},
     url = {http://geodesic.mathdoc.fr/articles/10.2298/FIL2214919B/}
}
TY  - JOUR
AU  - Ataouia Bakhtaoui
AU  - Faiza Limam-Belarbi
TI  - Local linear estimation of the trimmed regression for censored data
JO  - Filomat
PY  - 2022
SP  - 4919 
VL  - 36
IS  - 14
UR  - http://geodesic.mathdoc.fr/articles/10.2298/FIL2214919B/
DO  - 10.2298/FIL2214919B
LA  - en
ID  - 10_2298_FIL2214919B
ER  - 
%0 Journal Article
%A Ataouia Bakhtaoui
%A Faiza Limam-Belarbi
%T Local linear estimation of the trimmed regression for censored data
%J Filomat
%D 2022
%P 4919 
%V 36
%N 14
%U http://geodesic.mathdoc.fr/articles/10.2298/FIL2214919B/
%R 10.2298/FIL2214919B
%G en
%F 10_2298_FIL2214919B

Cité par Sources :