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Statistical estimation for a partially linear single-index model with errors in all variables

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  • Zhensheng Huang
  • Xin Zhao

Abstract

This article considers partially linear single-index models with errors in all variables. By using the Pseudo − θ method (Liang, Härdle, and Carroll 1999), local linear regression and simulation-extrapolation (SIMEX) technique (Cook and Stefanski 1994), we propose an efficient methodology to estimate the current model. Under certain conditions the asymptotic properties of proposed estimators are obtained. Some simulation experiments and an application are conducted to illustrate our proposed method.

Suggested Citation

  • Zhensheng Huang & Xin Zhao, 2019. "Statistical estimation for a partially linear single-index model with errors in all variables," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 48(5), pages 1136-1148, March.
    • Handle: RePEc:taf:lstaxx:v:48:y:2019:i:5:p:1136-1148
    DOI: 10.1080/03610926.2018.1425446
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