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Least Absolute Deviation Estimate for Functional Coefficient Partially Linear Regression Models

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  • Yanqin Feng
  • Guoxin Zuo
  • Li Liu

Abstract

The functional coefficient partially linear regression model is a useful generalization of the nonparametric model, partial linear model, and varying coefficient model. In this paper, the local linear technique and the method are employed to estimate all the functions in the functional coefficient partially linear regression model. The asymptotic properties of the proposed estimators are studied. Simulation studies are conducted to show the validity of the estimate procedure.

Suggested Citation

  • Yanqin Feng & Guoxin Zuo & Li Liu, 2012. "Least Absolute Deviation Estimate for Functional Coefficient Partially Linear Regression Models," Journal of Probability and Statistics, Hindawi, vol. 2012, pages 1-20, December.
    • Handle: RePEc:hin:jnljps:131085
    DOI: 10.1155/2012/131085
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