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February 2013 Simultaneous variable selection and estimation in semiparametric modeling of longitudinal/clustered data
Shujie Ma, Qiongxia Song, Li Wang
Bernoulli 19(1): 252-274 (February 2013). DOI: 10.3150/11-BEJ386

Abstract

We consider the problem of simultaneous variable selection and estimation in additive, partially linear models for longitudinal/clustered data. We propose an estimation procedure via polynomial splines to estimate the nonparametric components and apply proper penalty functions to achieve sparsity in the linear part. Under reasonable conditions, we obtain the asymptotic normality of the estimators for the linear components and the consistency of the estimators for the nonparametric components. We further demonstrate that, with proper choice of the regularization parameter, the penalized estimators of the non-zero coefficients achieve the asymptotic oracle property. The finite sample behavior of the penalized estimators is evaluated with simulation studies and illustrated by a longitudinal CD4 cell count data set.

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Shujie Ma. Qiongxia Song. Li Wang. "Simultaneous variable selection and estimation in semiparametric modeling of longitudinal/clustered data." Bernoulli 19 (1) 252 - 274, February 2013. https://doi.org/10.3150/11-BEJ386

Information

Published: February 2013
First available in Project Euclid: 18 January 2013

zbMATH: 1259.62021
MathSciNet: MR3019494
Digital Object Identifier: 10.3150/11-BEJ386

Rights: Copyright © 2013 Bernoulli Society for Mathematical Statistics and Probability

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Vol.19 • No. 1 • February 2013
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