Some wavelet filters to estimate non-parametric GAM models with application and simulation | ||
| IRAQI JOURNAL OF STATISTICAL SCIENCES | ||
| Article 2, Volume 17, Issue 32, Autumn 2020, Page 9-26 PDF (1214 K) | ||
| Document Type: Research Paper | ||
| DOI: 10.33899/iqjoss.2020.167385 | ||
| Authors | ||
Alaa Abulsattar Hamoodat  ; Bashar Abdulaziz AL-Talib | ||
| Department of Statistics and Informatics, Faculty of Computer Sciences and Mathematics, University of Mosul, Mosul, Iraq | ||
| Abstract | ||
| This study shed light on the method of estimating the GAM based on Smoothing splines repetitive graders . The Wavelet Shrinkage method was used as a paving of data when estimating the GAM by using some wavelets as filters in calculating the wavy intermittent transformation, including (Haar Wavelet, Daubecheis Wavelet, Coiflets Wavelet, wavelet Least Asymmetric) with one of the types of threshold cutting which is Soft Threshold Thresholding to obtain modified coefficients for intermittent wavelet transformation with explanatory and response variables and dependence on estimating the WGAM model with a comparison of the results of all methods with some comparative statistical criteria, And that is by employing the simulation method as well as through real data analysis, and for this purpose data was collected from Ibn Sina Teaching Hospital (Al-Wafa Specialist Center for Diabetes and Endocrinology Consultant Short Stature) for Nineveh Governorate - 2019, for cases of short stature, and a program was used R for the purpose of writing some code for the purpose of obtaining the desired results from this research. | ||
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