Wavelet shrinkage in estimation of regression function with error in variables
نویسندگان
1 Department of Statistics, Faculty of Science, Payame Noor University, Tehran, Iran
2 Department of Statistics, Faculty of Science, Gonbad Kavous University, Gonbad Kavous, Iran
3 Department of Statistics, Faculty of Science, Payame Noor University, Tehran, Iran
4 Department of Statistics, Faculty of Science, Payame Noor University, Tehran, Iran
doi
10.22075/ijnaa.2024.34558.5164چکیده
The purpose of this study was to estimate the unknown regression function $h$ in a regression model having errors-in-variables: $(Y,X)$, where $Y=h(U)+E$ and $X=U+T$. We propose a new adaptive estimator through the wavelet shrinkage method to estimate $h$. In particular, the block thresholding method has been investigated by considering some simple assumptions on $E$. Finally, using a simulation study, we have compared the proposed estimator with other threshold estimators.
