Gao, Jiti (1994): Asymptotic theory for partly linear models. Published in: Communications in Statistics: Theory and Methods , Vol. 24, No. 8 (7 April 1995): pp. 19852009.

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Abstract
This paper considers a partially linear model of the form y = x beta + g(t) + e, where beta is an unknown parameter vector, g(.) is an unknown function, and e is an error term. Based on a nonparametric estimate of g(.), the parameter beta is estimated by a semiparametric weighted least squares estimator. An asymptotic theory is established for the consistency of the estimators.
Item Type:  MPRA Paper 

Original Title:  Asymptotic theory for partly linear models 
English Title:  Asymptotic Theory for Partly Linear Models 
Language:  English 
Keywords:  Asymptotic normality, linear process, partly linear model, strong consistency 
Subjects:  C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C14  Semiparametric and Nonparametric Methods: General C  Mathematical and Quantitative Methods > C2  Single Equation Models ; Single Variables > C22  TimeSeries Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes 
Item ID:  40452 
Depositing User:  Jiti Gao 
Date Deposited:  04 Aug 2012 02:33 
Last Modified:  11 May 2016 03:35 
References:  Andrews, D. W. K., 1991 Asymptotic normality of series estimates for nonparametric and semiparametric regression models. Econometrica 59, 307  345. Ansley, C. F. and Wecker, W. E., 1983 Extensions and examples of signal extraction approach to regression. In Applied Time Series Analysis of Econometric Data. 181192. Bennett, G., 1962. Probability inequalities for sums of independent random variables. Journal of the American Association 57, 3345. Chen, H., 1988. Convergence rates for parametric components in a partly linear model. Annals of Statistics 16, 136146. Eubank, R., Hart, D. and Lariccia, V. N., 1993. Testing goodness of fit via nonparametric function estimation techniques. Communications in Statistics: Theory and Methods 22, 33273354. Gao, J. T., 1992. Theory of Large Sample in Semiparametric Regression Models. Doctoral Thesis, Graduate School of University of Science and Technology of China. Heckman, N., 1986. Spline smoothing in a partly linear model. Journal of the Royal Statistical Society Series B 48, 244248. Phillips, P. C. B. and Solo, V., 1992. Asymptotics for linear processes. Annals of Statistics 20, 9711001. Rice, J., 1986. Convergence rates for partially splined models. Statistics and Probability Letters 4, 203208. Speckman, P., 1988. Kernel smoothing in partial linear models. Journal of the Royal Statistical Society Series B 50, 413436. Wu, C. F., 1981. Asymptotic theory of nonlinear least squares estimate. Annals of Statistics 9, 501513. 
URI:  https://mpra.ub.unimuenchen.de/id/eprint/40452 