Wavelet estimation in nonparametric linear mixed-effects errors in variables model

Nonparametric linear mixed effects models are preferred due to overcome the restrictions of which need satisfy distributional assumptions. In these models, smoothing approaches needed handle nonparametric part and chosen according type data. When there is a measurement error in part, techniques become more complicated. this paper, we propose wavelet approach smooth function under known model then, predict random pa rameter. Fu rthermore, si mulation study done demonstrate theoretical findings by comparing with case ignoring error. The performances much better for proposed than no case.