Title :
Recursive nonparametric regression with errors in variables
Author :
Chen, Xing-Min ; Gao, Chao
Author_Institution :
School of Mathematical Sciences, Dalian University of Technology, Dalian 116024, P.R. China
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.
Keywords :
Bandwidth; Convergence; Deconvolution; Estimation; Kernel; Measurement errors; Noise; Errors in variables; kernel estimation; nonlinear regression; recursive estimation; strong consistency;
Conference_Titel :
Control Conference (CCC), 2015 34th Chinese
Conference_Location :
Hangzhou, China
DOI :
10.1109/ChiCC.2015.7259956
