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Small sample properties of the maximum likelihood estimator for low order ARFIMA models : a Monte Carlo simulation
Author
Source
Mu'tah Journal for Research and Studies : Natural and Applied Sciences Series
Issue
Vol. 16, Issue 3 (30 Sep. 2001), pp.193-204, 12 p.
Publisher
Mutah University Deanship of Academic Research
Publication Date
2001-09-30
Country of Publication
Jordan
No. of Pages
12
Main Subjects
Topics
Abstract AR
تهدف هذه الدراسة التي تعتمد على طريقة المحاكاة بتحليل الخصائص لثلاثة أنواع من تقديرات تعظيم الأرجحية على نماذج أقل الرتب للفروقات الكسرية للانحدار الذاتي و المتوسطات المتحركة.
هذه التقديرات هي : (1) تقدير تعظيم الأرجحية، الكاملة، (2) تقدير تعظيم الأرجحية المعدلة، (3) تقدير و ايتل لتعظيم الأرجحية، حيت أن طول السلسلة مئة مشاهدة.
و قد تم مقارنة هذه التقديرات باستخدام التأثير التراكمي و معدل الأخطاء و نسبة فترات الثقة.
و تشير نتائج هذه الدراسة على أن أفضل تقدير لتعظيم الأرجحية لهذه النماذج هو تقدير وايتل بينما تعظيم الأرجحية المعدل هو بديل لتقدير وايتل.
Abstract EN
We analyze by simulation the properties of three estimators for low order autoregressive fractionally integrated moving average model (ARFIMA (p,d,q)).
The estimators considered are the exact maximum likelihood estimator, EMLE, the Modified maximum likelihood estimator, MMLE, and the Whittle maximum likelihood estimator, WMLE.
The length of the series is 100.
The estimators are compared in terms of pile-up effect, mean square error, and percentage confidence level. The WMLE turns out to be a reliable estimator for ARIMA (p,d,q), when d = 0 and ARFIMA models.
Its small losses in performance in case of “easy” models are compensated sufficiently in more “difficult” models.
The MMLE is an alternative to the WMLE but is computationally more demanding.
It is either equivalent to the EMLE or more favorable than EMLE.
The EMLE, on the other hand, should only be used with care for fractionally integrated models due to its potential large negative of the fractional integration parameter.
In general, one should proceed with caution for AR1MA (1,0,1) models writh almost canceling roots, and, in particular, in case of the EMLE, and the MMLE, for inference in the vicinity of a moving average root of+1.
American Psychological Association (APA)
Hilan, Mahmud. 2001. Small sample properties of the maximum likelihood estimator for low order ARFIMA models : a Monte Carlo simulation. Mu'tah Journal for Research and Studies : Natural and Applied Sciences Series،Vol. 16, no. 3, pp.193-204.
https://search.emarefa.net/detail/BIM-377620
Modern Language Association (MLA)
Hilan, Mahmud. Small sample properties of the maximum likelihood estimator for low order ARFIMA models : a Monte Carlo simulation. Mu'tah Journal for Research and Studies : Natural and Applied Sciences Series Vol. 16, no. 3 (2001), pp.193-204.
https://search.emarefa.net/detail/BIM-377620
American Medical Association (AMA)
Hilan, Mahmud. Small sample properties of the maximum likelihood estimator for low order ARFIMA models : a Monte Carlo simulation. Mu'tah Journal for Research and Studies : Natural and Applied Sciences Series. 2001. Vol. 16, no. 3, pp.193-204.
https://search.emarefa.net/detail/BIM-377620
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 204
Record ID
BIM-377620