Re-sampling techniques in count data regression models
Other Title(s)
أساليب إعادة المعاينة في نماذج انحدار بيانات العد
Joint Authors
al-Jamal, Zakariyya Yahya
Rashid, Khayri B.
Source
Iraqi Journal of Statistical Science
Issue
Vol. 12, Issue 22 (31 Dec. 2012), pp.15-25, 11 p.
Publisher
University of Mosul College of Computer Science and Mathematics
Publication Date
2012-12-31
Country of Publication
Iraq
No. of Pages
11
Main Subjects
Topics
Abstract AR
تعد عملية نمذجة المتغيرات القابلة للعد من المهام المهمة في العديد من المجالات منها الاقتصادية و العلوم الاجتماعية و الطبية.
غالبا ما يستخدم نموذج انحدار بواسون لنمذجة مثل هذا النوع من البيانات و يكون هذا النموذج غير ملائم عندما يعاني من مشكلة (Overdispersion) و عليه سوف يستخدم نموذج انحدار ثنائي الحدين السالب.
Abstract EN
Modeling count variables is a common task in many application areas such as economics, social sciences, and medicine.
The classical Poisson regression model for count data is often used and it is limited in these disciplines since count data sets typically exhibit overdispersion, so negative binomial regression can be used.
We use a jackknife- after-bootstrap procedure to assess the error in the bootstrap estimated parameters.
The method is illustrated through two real examples.
The results suggest that the jackknife- after- bootstrap method provides a reliable alternative to traditional methods particularly in small to moderate samples.
American Psychological Association (APA)
al-Jamal, Zakariyya Yahya& Rashid, Khayri B.. 2012. Re-sampling techniques in count data regression models. Iraqi Journal of Statistical Science،Vol. 12, no. 22, pp.15-25.
https://search.emarefa.net/detail/BIM-321907
Modern Language Association (MLA)
al-Jamal, Zakariyya Yahya& Rashid, Khayri B.. Re-sampling techniques in count data regression models. Iraqi Journal of Statistical Science Vol. 12, no. 22 (2012), pp.15-25.
https://search.emarefa.net/detail/BIM-321907
American Medical Association (AMA)
al-Jamal, Zakariyya Yahya& Rashid, Khayri B.. Re-sampling techniques in count data regression models. Iraqi Journal of Statistical Science. 2012. Vol. 12, no. 22, pp.15-25.
https://search.emarefa.net/detail/BIM-321907
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 25
Record ID
BIM-321907