A Semi-parametric Regression Model with Errors in Variables

In this paper, we consider a partial linear regression model with measurement errors in possibly all the variables. We use a method of moments and deconvolution to construct a new class of parametric estimators together with a non-parametric kernel estimator. Strong convergence, optimal rate of weak convergence and asymptotic normality of the estimators are investigated. Copyright 2003 Board of the Foundation of the Scandinavian Journal of Statistics..