Local linear fitting under near epoch dependence: uniform consistency with convergence rates
Local linear fitting under near epoch dependence: uniform consistency with convergence rates
Local linear fitting is a popular nonparametric method in statistical and econometric modeling. Lu and Linton (2007, Econometric Theory23, 37–70) established the pointwise asymptotic distribution for the local linear estimator of a nonparametric regression function under the condition of near epoch dependence. In this paper, we further investigate the uniform consistency of this estimator. The uniform strong and weak consistencies with convergence rates for the local linear fitting are established under mild conditions. Furthermore, general results regarding uniform convergence rates for nonparametric kernel-based estimators are provided. The results of this paper will be of wide potential interest in time series semiparametric modeling.
935-958
Li, Degui
e341f702-23cd-4c1a-91a8-3b7aa3dfda15
Lu, Zudi
4aa7d988-ac2b-4150-a586-ca92b8adda95
Linton, Oliver
36fa04bf-d781-45bd-bd7f-c28f68e5df6e
October 2012
Li, Degui
e341f702-23cd-4c1a-91a8-3b7aa3dfda15
Lu, Zudi
4aa7d988-ac2b-4150-a586-ca92b8adda95
Linton, Oliver
36fa04bf-d781-45bd-bd7f-c28f68e5df6e
Li, Degui, Lu, Zudi and Linton, Oliver
(2012)
Local linear fitting under near epoch dependence: uniform consistency with convergence rates.
Econometric Theory, 28 (5), .
(doi:10.1017/S0266466612000011).
Abstract
Local linear fitting is a popular nonparametric method in statistical and econometric modeling. Lu and Linton (2007, Econometric Theory23, 37–70) established the pointwise asymptotic distribution for the local linear estimator of a nonparametric regression function under the condition of near epoch dependence. In this paper, we further investigate the uniform consistency of this estimator. The uniform strong and weak consistencies with convergence rates for the local linear fitting are established under mild conditions. Furthermore, general results regarding uniform convergence rates for nonparametric kernel-based estimators are provided. The results of this paper will be of wide potential interest in time series semiparametric modeling.
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Published date: October 2012
Organisations:
Mathematical Sciences
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Local EPrints ID: 356165
URI: http://eprints.soton.ac.uk/id/eprint/356165
PURE UUID: 4e31649e-c1bb-4043-a4be-2f65f785ed8f
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Date deposited: 28 Aug 2013 11:37
Last modified: 15 Mar 2024 03:49
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Author:
Degui Li
Author:
Oliver Linton
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