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Lv, Y.-Z., Zhang, R.-Q. and Huang, Z.-S. (2013) Estimation of Semi-Varying Coefficient Model with Surrogate Data and Validation Sampling. Acta Mathematicae Applicatae Sinica English, 29, 645-660. https://doi.org/10.1007/s10255-013-0241-3

has been cited by the following article:

• TITLE: Orthogonal Series Estimation of Nonparametric Regression Measurement Error Models with Validation Data

  AUTHORS: Zanhua Yin

  KEYWORDS: Ill-Posed Inverse Problems, Measurement Errors, Nonparametric Regression, Orthogonal Series, Validation Data

  JOURNAL NAME: Applied Mathematics, Vol.8 No.12, December 29, 2017

  ABSTRACT: In this article we study the estimation method of nonparametric regression measurement error model based on a validation data. The estimation procedures are based on orthogonal series estimation and truncated series approximation methods without specifying any structure equation and the distribution assumption. The convergence rates of the proposed estimator are derived. By example and through simulation, the method is robust against the misspecification of a measurement error model.