All Rights Reserved
AccessEcon LLC 2006, 2008.
Powered by MinhViet JSC
ralph lauren polo

 
Ke Yang
 
''An Improved Local-linear Estimator For Nonparametric Regression With Autoregressive Errors''
( 2013, Vol. 33 No.1 )
 
 
In this paper we propose a modification of the local linear smoother to account for the autocorrelated errors in a nonparametric regression model with random-design. The proposed estimator has a closed-form expression and is simple to calculate. The asymptotic bias and variance of the proposed estimator are studied for AR(1) case. Compared to the standard local linear smoother, the proposed estimator retains the same design-adaptive bias but has a smaller asymptotic variance. Therefore the proposed method improves the estimation efficiency in kernel regression
 
 
Keywords: Nonparametric method, Kernel regression, Local linear regression, autoregressive, Variance reduction
JEL: C1 - Econometric and Statistical Methods: General
C0 - Mathematical and Quantitative Methods: General
 
Manuscript Received : Jul 12 2012 Manuscript Accepted : Jan 08 2013

  This abstract has been downloaded 129 times                The Full PDF of this paper has been downloaded 87730 times