Regression models with correlated errors based on functional random design

• Karim Benhenni ^[1] ; Sonia Hedli-Griche ^[2] ; Mustapha Rachdi ^[1]
  1. [1] Grenoble Alpes University

     Grenoble Alpes University

     Arrondissement de Grenoble, Francia

     
  2. [2] University Ferhat Abbas of Setif

     University Ferhat Abbas of Setif

     Argelia

     
• Localización: Test: An Official Journal of the Spanish Society of Statistics and Operations Research, ISSN-e 1863-8260, ISSN 1133-0686, Vol. 26, Nº. 1, 2017, págs. 1-21
• Idioma: inglés
• DOI: 10.1007/s11749-016-0495-1
• Texto completo no disponible (Saber más ...)
• Resumen

  • This paper deals with the study of the estimation of the functional regression operator when the explanatory variable takes its values in some abstract space of functions. The main goal of this paper is to establish the exact rate of convergence of the mean squared error of the functional version of the Nadaraya–Watson kernel estimator when the errors come from a stationary process under long or short memory and based on random functional data. Moreover, these theoretical results are checked through some simulations with regular (smooth) and irregular curves and then with real data.