Advanced SearchSearch Tips
A comparison study on regression with stationary nonparametric autoregressive errors
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
A comparison study on regression with stationary nonparametric autoregressive errors
Yu, Kyusang;
  PDF(new window)
We compare four methods to estimate a regression coefficient under linear regression models with serially correlated errors. We assume that regression errors are generated with nonlinear autoregressive models. The four methods are: ordinary least square estimator, general least square estimator, parametric regression error correction method, and nonparametric regression error correction method. We also discuss some properties of nonlinear autoregressive models by presenting numerical studies with typical examples. Our numerical study suggests that no method dominates; however, the nonparametric regression error correction method works quite well.
nonparametric autoregressive model;regression;efficiency;
 Cited by
Bhattacharya, R. and Lee, C. (1995). Ergodicity of nonlinear first order autoregressive models, Journal of Theoretical Probability, 8, 210-219.

Biscay, R. J., Lavielle, M., and Ludena, C. (2005). Estimation of nonparametric autoregressive time series models under dynamical constraints, Journal of Time Series Analysis, 26, 371-397. crossref(new window)

Fan, J. and Gijbels, I. (1996). Local Polynomial Modelling and Its Applications, Chapman & Hall, London.

Haggan, V. and Ozaki, T. (1981). Modelling nonlinear random vibrations using an amplitude dependent autoregressive time series model, Biometrika, 68, 189-196. crossref(new window)

Sheather, S. (2009). A Modern Approach to Regression with R, Springer, New York.

Su, L. and Ullah, A. (2006). More efficient estimation in nonparametric regression with nonparametric autocorrelated errors, Econometric Theory, 22, 98-126.

Tong, H. (1990). Nonlinear Time Series: A Dynamical Approach, Oxford University Press, Oxford.

Tong, H. and Lim, K. (1980). Threshold autoregression, limit cycles and cyclical data (with Discussion), Journal of Royal Statistical Society B, 42, 245-292

Truong, Y. K. and Stone, C. (1992). Nonparametric function estimation involving time series, The Annals of Statistics, 20, 77-97. crossref(new window)