Table of Contents
Advances in Statistics
Volume 2015, Article ID 695904, 11 pages
Research Article

Estimation of the Derivatives of a Function in a Convolution Regression Model with Random Design

1Laboratoire de Mathématiques Nicolas Oresme, Université de Caen, BP 5186, 14032 Caen Cedex, France
2École Supérieure de Commerce IDRAC, 47 rue Sergent Michel Berthet, CP 607, 69258 Lyon Cedex 09, France

Received 8 August 2014; Revised 25 February 2015; Accepted 5 March 2015

Academic Editor: Jos De Brabanter

Copyright © 2015 Christophe Chesneau and Maher Kachour. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


A convolution regression model with random design is considered. We investigate the estimation of the derivatives of an unknown function, element of the convolution product. We introduce new estimators based on wavelet methods and provide theoretical guarantees on their good performances.