EconPapers    
Economics at your fingertips  
 

Asymptotic properties of the wavelet estimator in non parametric regression model with martingale difference errors

Xuejun Wang, Xin Deng and Yi Wu

Communications in Statistics - Theory and Methods, 2024, vol. 53, issue 9, 3312-3336

Abstract: This work mainly investigates the asymptotic properties for the wavelet estimator in a non parametric regression model with martingale difference random errors. The moment consistency, strong consistency, complete consistency, the rate of strong consistency and the asymptotic normality for the wavelet estimator are established under some mild conditions, which were not obtained before. Some numerical analysis is carried out to support the theoretical results.

Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2022.2152288 (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:53:y:2024:i:9:p:3312-3336

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

DOI: 10.1080/03610926.2022.2152288

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:53:y:2024:i:9:p:3312-3336