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Variable selection for varying coefficient models with measurement errors

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Abstract

This paper focuses on variable selections for varying coefficient models when some covariates are measured with errors. We present a bias-corrected variable selection procedure by combining basis function approximations with shrinkage estimations. With appropriate selection of the tuning parameters, we establish the consistency of the variable selection procedure, and derive the optimal convergence rate of the regularized estimators. A simulation study and a real data application are undertaken to assess the finite sample performance of the proposed variable selection procedure.

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Authors and Affiliations

  1. College of Applied Sciences, Beijing University of Technology, 100124, Beijing, China

    Peixin Zhao & Liugen Xue

  2. Department of Mathematics, Hechi University, 546300, Guangxi, Yizhou, China

    Peixin Zhao

Authors
  1. Peixin Zhao
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  2. Liugen Xue
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Correspondence to Peixin Zhao.

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Zhao, P., Xue, L. Variable selection for varying coefficient models with measurement errors. Metrika 74, 231–245 (2011). https://doi.org/10.1007/s00184-010-0300-1

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  • DOI: https://doi.org/10.1007/s00184-010-0300-1

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