Nonparametric linear mixed effects models are preferred due to overcome the restrictions of linear models which need to satisfy distributional assumptions. In these models, smoothing approaches are needed to handle nonparametric part and chosen according to the type of data. When there is a measurement error in the nonparametric part, these smoothing techniques become more complicated. In this paper, we propose wavelet approach to smooth nonparametric function under known measurement error in nonparametric linear mixed effects model and then, we predict random effects pa rameter. Fu rthermore, a si mulation study is done to demonstrate the theoretical findings by comparing with the case ignoring measurement error. The performances are much better for the proposed model than the no measurement error case.
Nonparametric Linear Mixed Effects Model Measurement Error; Errors-in-Variables Wavelet Estimation Wavelet Predictor*
| Primary Language | English |
|---|---|
| Subjects | Engineering |
| Journal Section | Research Article |
| Authors | |
| Submission Date | February 10, 2021 |
| Publication Date | October 9, 2022 |
| IZ | https://izlik.org/JA98ES95LC |
| Published in Issue | Year 2022 Volume: 40 Issue: 3 |
IMPORTANT NOTE: JOURNAL SUBMISSION LINK https://eds.yildiz.edu.tr/sigma/