On robust nonparametric regression estimation for a functional regressor

Nadjia Azzedine, Ali Laksaci and Elias Ould-Saïd

Statistics & Probability Letters, 2008, vol. 78, issue 18, 3216-3221

Abstract: We study a family of robust nonparametric estimators for a regression function based on a kernel method when the regressors are functional random variables. We establish the almost complete convergence rate of these estimators under the probability measure's concentration property on small balls of the functional variable. Simulations are given to show our estimator's behavior and the prediction quality for functional data.

Date: 2008
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167-7152(08)00301-5
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:stapro:v:78:y:2008:i:18:p:3216-3221

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

Access Statistics for this article

Statistics & Probability Letters is currently edited by Somnath Datta and Hira L. Koul

More articles in Statistics & Probability Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().