Comparing some of robust the non-parametric methods for semi-parametric regression models estimation
Other Title(s)
مقارنة بعض الطرائق اللامعلمية الحصينة لتقدير أنموذج الانحدار شبه المعلمي
Joint Authors
Bahiz, Zahra Khalid
Rashid, Husam Abd al-Razaq
Source
Journal of Economics and Administrative Science
Issue
Vol. 28, Issue 132 (30 Apr. 2022), pp.105-117, 13 p.
Publisher
University of Baghdad College of Administration and Economics
Publication Date
2022-04-30
Country of Publication
Iraq
No. of Pages
13
Main Subjects
Economics & Business Administration
Topics
Abstract AR
في هذا البحث تم استعمال بعض الطرائق اللامعلمية الحصينة لتقدير أنموذج الانحدار شبه المعلمي ومن ثم مقارنة هذه الطرائق بالاعتماد على معيار المقارنة الـ MSE اذ تم استعمال احجام عينات ومستويات تباين ونسب تلوث مختلفة وثلاثة نماذج مختلفة وهذه الطرائق تمثلت بطريقة (S-LLS) S-Estimation-Local Smoothing و(M-LLS) M-Estimation-Local Smoothing و(S-NW) S-Estimation- Nadarya_Watson Smoothing و(M-NW) M-Estimation-Nadarya-Watson Smoothing.واثبتت النتائج في الانموذج الاول ان طريقة (S-LLS) كانت هي الافضل في حالة احجام العينات الكبيرة وعند احجام العينات الصغيرة تبين ان طريقة (M-LLS) هي الافضل اما الانموذج الثاني تبين بشكل عام ان طريقة S-LLS هي الافضل بالاضافة الى طريقة M-LLS هي الافضل في بعض حالات احجام العينات وعند مستويات تباين مختلفة اما الانموذج الثالث تبين من خلال النتائج ان اغلب الحالات طريقة S-LLS هي الافضل بالاضافة طريقة M-LLS افضل في بعض حالات احجام العينات وعند مستويات تباين مختلفة
Abstract EN
In this research, some robust non-parametric methods were used to estimate the semi-parametric regression model, and then these methods were compared using the MSE comparison criterion, different sample sizes, levels of variance, pollution rates, and three different models were used.
These methods are S-LLS S-Estimation -local smoothing, (M-LLS)M- Estimation -local smoothing, (S-NW) S-Estimation-NadaryaWatson Smoothing, and (M-NW) M-Estimation-Nadarya-Watson Smoothing.
The results in the first model proved that the (S-LLS) method was the best in the case of large sample sizes, and small sample sizes showed that the (M-LLS) method was the best, while the second model showed in general that the S-LLS method was the best in addition to the method M-LLS was the best in some cases of sample sizes and at different levels of variance.
As for the third model, it was shown through the results that in most cases the S-LLS method was the best in addition to the M-LLS method which was better in some cases of sample sizes and at different levels of variance
American Psychological Association (APA)
Bahiz, Zahra Khalid& Rashid, Husam Abd al-Razaq. 2022. Comparing some of robust the non-parametric methods for semi-parametric regression models estimation. Journal of Economics and Administrative Science،Vol. 28, no. 132, pp.105-117.
https://search.emarefa.net/detail/BIM-1401144
Modern Language Association (MLA)
Bahiz, Zahra Khalid& Rashid, Husam Abd al-Razaq. Comparing some of robust the non-parametric methods for semi-parametric regression models estimation. Journal of Economics and Administrative Science Vol. 28, no. 132 (2022), pp.105-117.
https://search.emarefa.net/detail/BIM-1401144
American Medical Association (AMA)
Bahiz, Zahra Khalid& Rashid, Husam Abd al-Razaq. Comparing some of robust the non-parametric methods for semi-parametric regression models estimation. Journal of Economics and Administrative Science. 2022. Vol. 28, no. 132, pp.105-117.
https://search.emarefa.net/detail/BIM-1401144
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 115-116
Record ID
BIM-1401144