Abstract
Local linear fitting is a popular nonparametric method in statistical and econometric Modeling. Lu and Linton (2007, Econometric Theory 23, 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.
Original language | English |
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Pages (from-to) | 935-958 |
Number of pages | 24 |
Journal | Econometric Theory |
Volume | 28 |
Issue number | 5 |
DOIs | |
Publication status | Published - Oct 2012 |
Keywords
- GEOMETRIC ERGODICITY
- WEAK DEPENDENCE
- KERNEL ESTIMATION
- ESTIMATORS
- SEQUENCES
- NONLINEAR TIME-SERIES
- MODELS
- REGRESSION
- ASYMPTOTIC NORMALITY
- VARIABLES