مورد إلكتروني
An Improved Divergence Information Criterion for the Determination of the Order of an AR Process
| العنوان: | An Improved Divergence Information Criterion for the Determination of the Order of an AR Process |
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| بيانات النشر: | University of Lund University of Cyprus, Cyprus University of Cyprus, Cyprus Taylor & Francis 2010 |
| تفاصيل مُضافة: | Mantalos, Panagiotis Mattheou, K. Karagrigoriou, A. |
| نوع الوثيقة: | Electronic Resource |
| مستخلص: | In this article we propose a modification of the recently introduced divergence information criterion (DIC, Mattheou et al., 2009) for the determination of the order of an autoregressive process and show that it is an asymptotically unbiased estimator of the expected overall discrepancy, a nonnegative quantity that measures the distance between the true unknown model and a fitted approximating model. Further, we use Monte Carlo methods and various data generating processes for small, medium, and large sample sizes in order to explore the capabilities of the new criterion in selecting the optimal order in autoregressive processes and in general in a time series context. The new criterion shows remarkably good results by choosing the correct model more frequently than traditional information criteria. |
| مصطلحات الفهرس: | AR process, Information criterion, Measure of divergence, Model selection, 62M10, 62F07, 91B84, 94A15, Probability Theory and Statistics, Sannolikhetsteori och statistik, Article in journal, info:eu-repo/semantics/article, text |
| DOI: | 10.1080.03610911003650391 |
| URL: | Communications in statistics. Simulation and computation, 0361-0918, 2010, 39:5, s. 865-879 |
| الإتاحة: | Open access content. Open access content info:eu-repo/semantics/restrictedAccess |
| ملاحظة: | English |
| أرقام أخرى: | UPE oai:DiVA.org:lnu-50573 doi:10.1080/03610911003650391 ISI:000277568500001 Scopus 2-s2.0-77952391452 1233513256 |
| المصدر المساهم: | UPPSALA UNIV LIBR From OAIster®, provided by the OCLC Cooperative. |
| رقم الانضمام: | edsoai.on1233513256 |
| قاعدة البيانات: | OAIster |
| DOI: | 10.1080.03610911003650391 |
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