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2011 A difference based approach to the semiparametric partial linear model
Lie Wang, Lawrence D. Brown, T. Tony Cai
Electron. J. Statist. 5: 619-641 (2011). DOI: 10.1214/11-EJS621

Abstract

A commonly used semiparametric partial linear model is considered. We propose analyzing this model using a difference based approach. The procedure estimates the linear component based on the differences of the observations and then estimates the nonparametric component by either a kernel or a wavelet thresholding method using the residuals of the linear fit. It is shown that both the estimator of the linear component and the estimator of the nonparametric component asymptotically perform as well as if the other component were known. The estimator of the linear component is asymptotically efficient and the estimator of the nonparametric component is asymptotically rate optimal. A test for linear combinations of the regression coefficients of the linear component is also developed. Both the estimation and the testing procedures are easily implementable. Numerical performance of the procedure is studied using both simulated and real data. In particular, we demonstrate our method in an analysis of an attitude data set.

Citation

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Lie Wang. Lawrence D. Brown. T. Tony Cai. "A difference based approach to the semiparametric partial linear model." Electron. J. Statist. 5 619 - 641, 2011. https://doi.org/10.1214/11-EJS621

Information

Published: 2011
First available in Project Euclid: 27 June 2011

zbMATH: 1329.62179
MathSciNet: MR2813557
Digital Object Identifier: 10.1214/11-EJS621

Subjects:
Primary: 60K35

Rights: Copyright © 2011 The Institute of Mathematical Statistics and the Bernoulli Society

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