EconPapers    
Economics at your fingertips  
 

Nonparametric regression method with functional covariates and multivariate response

Kurdistan M. Taher Omar and Bo Wang

Communications in Statistics - Theory and Methods, 2019, vol. 48, issue 2, 368-380

Abstract: Nonparametric regression methods have been widely studied in functional regression analysis in the context of functional covariates and univariate response, but it is not the case for functional covariates with multivariate response. In this paper, we present two new solutions for the latter problem: the first is to directly extend the nonparametric method for univariate response to multivariate response, and in the second, the correlation among different responses is incorporated into the model. The asymptotic properties of the estimators are studied, and the effectiveness of the proposed methods is demonstrated through several simulation studies and a real data example.

Date: 2019
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2017.1410716 (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:lstaxx:v:48:y:2019:i:2:p:368-380

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/lsta20

DOI: 10.1080/03610926.2017.1410716

Access Statistics for this article

Communications in Statistics - Theory and Methods is currently edited by Debbie Iscoe

More articles in Communications in Statistics - Theory and Methods from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-20
Handle: RePEc:taf:lstaxx:v:48:y:2019:i:2:p:368-380