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Using the wavelet analysis to estimate the nonparametric regression model in the presence of associated errors | ||
| International Journal of Nonlinear Analysis and Applications | ||
| مقاله 152، دوره 13، شماره 1، خرداد 2022، صفحه 1855-1862 اصل مقاله (435.77 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22075/ijnaa.2022.5816 | ||
| نویسندگان | ||
| Mohmmed Salh AbduAlkareem Mahdi* 1؛ Saad Kadem Hamza2 | ||
| 1Ministry of Interior, Directorate of Human Recourses, Iraq | ||
| 2Department of Statistics, College of Administration and Economics University of Baghdad, Baghdad, Iraq | ||
| تاریخ دریافت: 09 مهر 1400، تاریخ پذیرش: 09 آبان 1400 | ||
| چکیده | ||
| The wavelet shrink estimator is an attractive technique when estimating the nonparametric regression functions, but it is very sensitive in the case of a correlation in errors. In this research, a polynomial model of low degree was used for the purpose of addressing the boundary problem in the wavelet reduction in addition to using flexible threshold values in the case of Correlation in errors as it deals with those transactions at each level separately, unlike the comprehensive threshold values that deal with all levels simultaneously, as (Visushrink) methods, (False Discovery Rate) method, (Improvement Thresholding) and (Sureshrink method), as the study was conducted on real monthly data represented in the rates of theft crimes for juveniles in Iraq, specifically the Baghdad governorate, and the risk ratios about those crimes for the years 2008-2018, with a sample size of (128) (Sureshrink) The study also showed an increase in the rate of theft crimes for juveniles in recent years. | ||
| کلیدواژه‌ها | ||
| Discrete Wavelet Transformation؛ Threshold Value؛ Wavelet Shrinkage؛ Correlated | ||
| مراجع | ||
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