REGRESSION NON PARAMETRIQUE DANS UN MODELE GAUSSIEN

Authors

  • N NEMOUCHI Université Constantine 1
  • Z MOHDEB Université Constantine 1

Keywords:

Estimation de la densité, estimation de la régression, estimation à noyau, bandes de confiance.

Abstract

L'objet de ce travail est de construire des estimateurs de régression non paramétrique asymptotiquement optimaux, sous l'hypothèse que les lois sous-jacentes sont gaussiennes. Les résultats que nous obtenons présentent l'intérêt d'être directement applicables en analyse exploratoire des données.

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Author Biographies

N NEMOUCHI, Université Constantine 1

Département de Mathématique

Z MOHDEB, Université Constantine 1

Département de Mathématique,

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Published

2006-12-01

How to Cite

NEMOUCHI, N., & MOHDEB, Z. (2006). REGRESSION NON PARAMETRIQUE DANS UN MODELE GAUSSIEN. Sciences & Technology. A, Exactes Sciences, (24), 25–30. Retrieved from https://revue.umc.edu.dz/a/article/view/136

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