论文摘要：We study semiparametric varying-coefficient partially linear models when some
linear covariates are not observed, but ancillary variables are available.Semiparametric profile-likelihood estimation procedures are developed for parametric and nonparametric components after we calibrate the error-prone covariates. Asymptotic properties of the proposed estimators are established. We also propose the profile likelihood ratio test and Wald test to identify significant parametric and nonparametric components. To improve accuracy of the proposed tests for small or moderate sample sizes, Wild bootstrap version is also proposed to calculate the critical values. Intensive simulation experiments are conducted to illustrate the proposed approaches.
论文题目: Statistical Inference for Semi-parametric Varying-coefficient Partially Linear Models with Error-prone Linear Covariates
论文作者: Zhou, Y. and Liang H
发表刊物: Annals of Statistics
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