In this note, we investigate the kernel-type estimator of the nonparametric expectile regression model for functional data. More precisely, we establish the almost complete convergence rate of this estimator under some mild conditions. Finally, the usefulness of the expectile regression is discussed, in particular, the connection with the regression function.
Dans cette note, nous nous intéressons au problème d’estimation non-paramétrique de la fonction de régression expectile lorsqu’on régresse une variable réelle sur une variable fonctionnelle. Plus précisément, nous obtenons la convergence presque complète de l’estimateur à noyau de la fonction de régression expectile sous des conditions générales. Nous discutons brièvement notre résultat et mettons en évidence le lien avec la fonction de régression.
Revised:
Accepted:
Published online:
Mustapha Mohammedi 1; Salim Bouzebda 2; Ali Laksaci 3
@article{CRMATH_2020__358_3_267_0, author = {Mustapha Mohammedi and Salim Bouzebda and Ali Laksaci}, title = {On the nonparametric estimation of the functional expectile regression}, journal = {Comptes Rendus. Math\'ematique}, pages = {267--272}, publisher = {Acad\'emie des sciences, Paris}, volume = {358}, number = {3}, year = {2020}, doi = {10.5802/crmath.27}, language = {en}, }
TY - JOUR AU - Mustapha Mohammedi AU - Salim Bouzebda AU - Ali Laksaci TI - On the nonparametric estimation of the functional expectile regression JO - Comptes Rendus. Mathématique PY - 2020 SP - 267 EP - 272 VL - 358 IS - 3 PB - Académie des sciences, Paris DO - 10.5802/crmath.27 LA - en ID - CRMATH_2020__358_3_267_0 ER -
Mustapha Mohammedi; Salim Bouzebda; Ali Laksaci. On the nonparametric estimation of the functional expectile regression. Comptes Rendus. Mathématique, Volume 358 (2020) no. 3, pp. 267-272. doi : 10.5802/crmath.27. https://comptes-rendus.academie-sciences.fr/mathematique/articles/10.5802/crmath.27/
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