Time series forecasting with UCM model : a comparative study using the Tigris River data
Other Title(s)
تكهن السلاسل الزمنية بنموذج UCM : دراسة مقارنة باستخدام بيانات نهر دجلة
Joint Authors
Muttar, Zafir Ramadan
Husayn, Ilham Abd al-Karim
Source
Iraqi Journal of Statistical Science
Issue
Vol. 8, Issue 14 (31 Dec. 2008), pp.32-47, 16 p.
Publisher
University of Mosul College of Computer Science and Mathematics
Publication Date
2008-12-31
Country of Publication
Iraq
No. of Pages
16
Main Subjects
Topics
Abstract AR
يتناول هذا البحث بناء نموذجين رياضيين أساسيين للتكهن بتدفق مياه نهر دجلة الداخلة إلى مدينة الموصل, الأول هو نموذج المكونات غير المشاهدة Unobserved Components Model و الذي يرمز له بـ UCM و الثاني هو نموذج الانحدار الذاتي و المتوسطات المتحركة Autoregressive and Moving Average و الذي يرمز له بـ ARMA, إذ تم بناء 10 نماذج أولية من نماذج ARMA لبيانات السلسلة الزمنية لتدفق نهر دجلة بعد تحويل هذه البيانات إلى الصيغة القياسية للتخلص من التأثيرات الموسمية, و كان أفضل نموذج يمثل البيانات من هذه النماذج هو نموذج ARMA (2,2) اعتمادا على معيار أكاكي المصحح بينما كان نموذج ARMA (1,2) أفضل نموذج تكهني لامتلاكه أقل قيمة لمتوسط الخطأ المطلق Mean Absolute Error و الذي يرمز له بالرمز MAE و تم التوصل إلى أن نتائج التكهن بنموذج UCM أفضل من نتائج التكهن بنموذج ARMA اعتمادا على المعيار الإحصائي MAE.
Abstract EN
In this paper, we build two basic models to forecast a flow water of the Tigris river which enters to mosul city.
The first model is Unobserved Components Model which is abbreviated as UCM, the second is Autoregressive and Moving Average model which is mentioned as ARMA, we built 10 primary models from ARMA to data of the time series of flow Tigris river after we transfer the data to a standrized form to remove seasonal effects.
The best model which represented the data among ARMA models which are mentionted above is ARMA (2, 2) by depending on the correction of Akaike information criterion which is symbolized by AICc.
while ARMA(1, 2) model is the best model for forecasting because it has a minimum mean absolute error which is symbolized by MAE.
We obtained that the forecasting of flow water by UCM model is better than the results of ARMA (1, 2) model by depending on the criterion MAE.
American Psychological Association (APA)
Muttar, Zafir Ramadan& Husayn, Ilham Abd al-Karim. 2008. Time series forecasting with UCM model : a comparative study using the Tigris River data. Iraqi Journal of Statistical Science،Vol. 8, no. 14, pp.32-47.
https://search.emarefa.net/detail/BIM-332120
Modern Language Association (MLA)
Muttar, Zafir Ramadan& Husayn, Ilham Abd al-Karim. Time series forecasting with UCM model : a comparative study using the Tigris River data. Iraqi Journal of Statistical Science Vol. 8, no. 14 (2008), pp.32-47.
https://search.emarefa.net/detail/BIM-332120
American Medical Association (AMA)
Muttar, Zafir Ramadan& Husayn, Ilham Abd al-Karim. Time series forecasting with UCM model : a comparative study using the Tigris River data. Iraqi Journal of Statistical Science. 2008. Vol. 8, no. 14, pp.32-47.
https://search.emarefa.net/detail/BIM-332120
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 47
Record ID
BIM-332120