Comptes Rendus
Statistics
On the nonparametric estimation of the functional expectile regression
Comptes Rendus. Mathématique, Volume 358 (2020) no. 3, pp. 267-272.

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.

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DOI: 10.5802/crmath.27

Mustapha Mohammedi 1; Salim Bouzebda 2; Ali Laksaci 3

1 Université Djillali Liabès, BP 89, 22000, Sidi Bel Abbès, Algérie, L.S.P.S., Sidi Bel Abbès, Algérie
2 Alliance Sorbonne Université, Université de Technologie de Compiègne, L.M.A.C., Compiègne, France
3 Department of Mathematics, College of Science, Unit for Statistical Research and Studies Support, King Khalid University, P.O. Box 9004, Abha 62529, Saudi Arabia
License: CC-BY 4.0
Copyrights: The authors retain unrestricted copyrights and publishing rights
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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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