Estimation in semiparametric time series regression

Chen, Jia, Gao, Jiti and Li, Degui (2011) Estimation in semiparametric time series regression. Statistics and its Interface, 4 2: 243-251.

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Name Description MIMEType Size Downloads
Author Chen, Jia
Gao, Jiti
Li, Degui
Title Estimation in semiparametric time series regression
Journal name Statistics and its Interface   Check publisher's open access policy
ISSN 1938-7989
Publication date 2011-01-01
Sub-type Article (original research)
Open Access Status Not Open Access
Volume 4
Issue 2
Start page 243
End page 251
Total pages 9
Place of publication Somerville, MA, United States
Publisher International Press
Language eng
Formatted abstract
In this paper, we consider a semiparametric time series regression model and establish a set of identification conditions such that the model under discussion is both identifiable and estimable. We estimate the parameters in the model by using the method of moment and the nonlinear function by using the local linear method, and establish the asymptotic distributions for the proposed estimators. We then discuss how to estimate a sequence of local departure functions nonparametrically when the null hypothesis is rejected and establish some related asymptotic theory. Both the simulation study and the empirical application are also provided to illustrate the finite sample behavior of the proposed models and methods.
Keyword Asymptotic distribution
Departure function
Local linear method
Semiparametric modelling
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Mathematics and Physics
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Citation counts: TR Web of Science Citation Count  Cited 2 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 2 times in Scopus Article | Citations
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Created: Fri, 02 Sep 2011, 00:23:12 EST by Dr Jia Chen on behalf of Mathematics