Estimation in Varying-Coefficient Errors-in-Variables Models with Missing Response Variables

Abstract

Abstract This article is concerned with the estimation of a varying-coefficient regression model when the response variable is sometimes missing and some of the covariates are measured with additive errors. We propose a class of estimators for the coefficient functions, as well as for the population mean and the error variance. The resulting estimators are shown to be asymptotically normal. Simulation studies are conducted to illustrate our approach. Keywords: Asymptotic normalityMeasurement errorMissing dataVarying coefficient modelsMathematics Subject Classification: 62G05 Acknowledgments The research was supported by The Philosophy and Social Science Foundation of China (No. 07CTJ003), and “211” Project Foundation of Minzu University of China (No. 021211030312).