Estimation of Partially Linear Regression for Errors-in-Variables Models with Validation Data

摘要

This paper develops an estimation approach for error-in-covariables partially linear model with the help of validation data. A feasible least squares estimator of the parameter is denned by means of local linear kernel estimator. Further, the estimator of non-parametric component is also defined by the Fourier transformation method. A small simulation studies are given and the convergent behaviors for the proposed parametric and nonparametric estimators are shown respectively.