EconPapers    
Economics at your fingertips  
 

Robust nonparametric estimation for functional data

C. Crambes, L. Delsol and A. Laksaci

Journal of Nonparametric Statistics, 2008, vol. 20, issue 7, 573-598

Abstract: Robust estimation provides an alternative approach to classical methods, for instance, when the data are affected by the presence of outliers. Recently, these robust estimators have been considered for models with functional data. In this paper, we focus on asymptotic properties of a conditional nonparametric estimation of a real-valued variable with a functional covariate. We present results dealing with 𝕃q errors of these estimators. Then, our estimation procedure is evaluated by means of some applications to real data sets.

Date: 2008
References: Add references at CitEc
Citations: View citations in EconPapers (10)

Downloads: (external link)
http://hdl.handle.net/10.1080/10485250802331524 (text/html)
Access to full text is restricted to subscribers.

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:taf:gnstxx:v:20:y:2008:i:7:p:573-598

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/GNST20

DOI: 10.1080/10485250802331524

Access Statistics for this article

Journal of Nonparametric Statistics is currently edited by Jun Shao

More articles in Journal of Nonparametric Statistics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst (chris.longhurst@tandf.co.uk).

 
Page updated 2024-12-29
Handle: RePEc:taf:gnstxx:v:20:y:2008:i:7:p:573-598