Recursive nonparametric regression with errors in variables

Abstract

Recursive estimation for nonparametric regression with errors in variables is considered in this paper. Based on the deconvolution kernel, recursive estimate for the regression function is given. Strong consistency is established when observation noises are ordinary smooth or supper smooth. Finally a numerical simulation is provided to justify the theoretical analysis.