A Nonparametric Regression Estimator that Adapts to Error Distribution of Unknown Form
AbstractWe propose a new estimator for nonparametric regression based on local likelihood estimation using an estimated error score function obtained from the residuals of a preliminary nonparametric regression. We show that our estimator is asymptotically equivalent to the infeasible local maximum likelihood estimator [Staniswalis (1989)], and hence improves on standard kernel estimators when the error distribution is not normal. We investigate the finite sample performance of our procedure on simulated data.
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Bibliographic InfoPaper provided by Suntory and Toyota International Centres for Economics and Related Disciplines, LSE in its series STICERD - Econometrics Paper Series with number /2001/419.
Date of creation: Jun 2001
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Web page: http://sticerd.lse.ac.uk/_new/publications/default.asp
Adaptive estimation; asymptotic expansions; efficiency; kernel; local likelihood estimation; nonparametric regression.;
Other versions of this item:
- Linton, Oliver & Xiao, Zhijie, 2007. "A Nonparametric Regression Estimator That Adapts To Error Distribution Of Unknown Form," Econometric Theory, Cambridge University Press, vol. 23(03), pages 371-413, June.
- Linton, Oliver Bruce & Xiao, Zhijie, 2001. "A nonparametric regression estimator that adapts to error distribution of unknown form," SFB 373 Discussion Papers 2001,33, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
- Oliver Linton & Zhijie Xiao, 2001. "A nonparametric regression estimator that adapts to error distribution of unknown form," LSE Research Online Documents on Economics 2120, London School of Economics and Political Science, LSE Library.
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Gozalo, Pedro & Linton, Oliver, 2000. "Local nonlinear least squares: Using parametric information in nonparametric regression," Journal of Econometrics, Elsevier, vol. 99(1), pages 63-106, November.
- Zhang, Xibin & King, Maxwell L. & Shang, Han Lin, 2014.
"A sampling algorithm for bandwidth estimation in a nonparametric regression model with a flexible error density,"
Computational Statistics & Data Analysis,
Elsevier, vol. 78(C), pages 218-234.
- Xibin Zhang & Maxwell L. King & Han Lin Shang, 2013. "A sampling algorithm for bandwidth estimation in a nonparametric regression model with a flexible error density," Monash Econometrics and Business Statistics Working Papers 20/13, Monash University, Department of Econometrics and Business Statistics.
- Wang, Dong, 2010. "Modeling epigenetic modifications under multiple treatment conditions," Computational Statistics & Data Analysis, Elsevier, vol. 54(4), pages 1179-1189, April.
- Yao, Weixin, 2013. "A note on EM algorithm for mixture models," Statistics & Probability Letters, Elsevier, vol. 83(2), pages 519-526.
- Xibin Zhang & Maxwell L. King & Han Lin Shang, 2011. "Bayesian estimation of bandwidths for a nonparametric regression model with a flexible error density," Monash Econometrics and Business Statistics Working Papers 10/11, Monash University, Department of Econometrics and Business Statistics.
- Wang, Qin & Yao, Weixin, 2012. "An adaptive estimation of MAVE," Journal of Multivariate Analysis, Elsevier, vol. 104(1), pages 88-100, February.
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