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Forecasting ARMA models: A comparative study of information criteria focusing on MDIC

dc.contributor.authorMantalos, Panagiotisen
dc.contributor.authorMattheou, K.en
dc.contributor.authorKaragrigoriou, Alexen
dc.creatorMantalos, Panagiotisen
dc.creatorMattheou, K.en
dc.creatorKaragrigoriou, Alexen
dc.date.accessioned2019-12-02T10:36:52Z
dc.date.available2019-12-02T10:36:52Z
dc.date.issued2010
dc.identifier.urihttp://gnosis.library.ucy.ac.cy/handle/7/57257
dc.description.abstractThis paper deals with the implementation of model selection criteria to data generated by ARMA processes. The recently introduced modified divergence information criterion is used and compared with traditional selection criteria like the Akaike information criterion (AIC) and the Schwarz information criterion (SIC). The appropriateness of the selected model is tested for one- and five-step ahead predictions with the use of the normalized mean squared forecast errors (NMSFE). © 2010 Taylor & Francis.en
dc.sourceJournal of Statistical Computation and Simulationen
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-77649139313&doi=10.1080%2f00949650802464137&partnerID=40&md5=6570531d271d9e708e591b9992dd6343
dc.subjectModel selectionen
dc.subjectInformation criterionen
dc.subjectARMA processen
dc.subjectMDICen
dc.subjectNMSFEen
dc.titleForecasting ARMA models: A comparative study of information criteria focusing on MDICen
dc.typeinfo:eu-repo/semantics/article
dc.identifier.doi10.1080/00949650802464137
dc.description.volume80
dc.description.issue1
dc.description.startingpage61
dc.description.endingpage73
dc.author.facultyΣχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences
dc.author.departmentΤμήμα Μαθηματικών και Στατιστικής / Department of Mathematics and Statistics
dc.type.uhtypeArticleen
dc.description.notes<p>Cited By :3</p>en
dc.source.abbreviationJ.Stat.Comput.Simul.en
dc.contributor.orcidKaragrigoriou, Alex [0000-0002-4919-2133]
dc.contributor.orcidMantalos, Panagiotis [0000-0002-8425-3990]
dc.gnosis.orcid0000-0002-4919-2133
dc.gnosis.orcid0000-0002-8425-3990


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