Wavelet shrinkage in estimation of regression function with error in variables | ||
| International Journal of Nonlinear Analysis and Applications | ||
| مقاله 8، دوره 16، شماره 11، بهمن 2025، صفحه 101-109 اصل مقاله (512.73 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22075/ijnaa.2024.34558.5164 | ||
| نویسندگان | ||
| Ghodratollah Rahmati* 1؛ Esmaeil Shirazi2؛ Masoud Yarmohammadi1؛ Parviz Nasiri3 | ||
| 1Department of Statistics, Faculty of Science, Payame Noor University, Tehran, Iran | ||
| 2Department of Statistics, Faculty of Science, Gonbad Kavous University, Gonbad Kavous, Iran | ||
| 3Department of Statistics, Faculty of Science, Payame Noor University, Tehran, Iran | ||
| چکیده | ||
| 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. | ||
| کلیدواژهها | ||
| Block Thresholding Method؛ Error in Variable؛ Nonparametric Regression؛ Shrinkage Method؛ Wavelets | ||
| مراجع | ||
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