Wavelet-M-Estimation for Time-Varying Coefficient Time Series Models
Xingcai Zhou and
Fangxia Zhu
Discrete Dynamics in Nature and Society, 2020, vol. 2020, 1-11
Abstract:
This paper proposes wavelet-M-estimation for time-varying coefficient time series models by using a robust-type wavelet technique, which can adapt to local features of the time-varying coefficients and does not require the smoothness of the unknown time-varying coefficient. The wavelet-M-estimation has the desired asymptotic properties and can be used to estimate conditional quantile and to robustify the usual mean regression. Under mild assumptions, the Bahadur representation and the asymptotic normality of wavelet-M-estimation are established.
Date: 2020
References: Add references at CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://downloads.hindawi.com/journals/DDNS/2020/1025452.pdf (application/pdf)
http://downloads.hindawi.com/journals/DDNS/2020/1025452.xml (text/xml)
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:hin:jnddns:1025452
DOI: 10.1155/2020/1025452
Access Statistics for this article
More articles in Discrete Dynamics in Nature and Society from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().