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Information complexity criterion for order determination in autoregressive models

dc.contributor.authorAşıkgil, Barış
dc.date.accessioned2022-06-08T18:38:19Z
dc.date.available2022-06-08T18:38:19Z
dc.date.issued2011
dc.identifier.issn1303-5010
dc.identifier.issn2651-477X
dc.identifier.urihttps://hdl.handle.net/20.500.14124/730
dc.description.abstractAutoregressive models which include lags of the dependent variable are usually used in time series analysis. The corelogram of the series and some information criteria can be used in order to determine the order of these models. In this paper the information complexity criterion is considered for autoregressive time series models. A simulation study is performed in order to examine the performance of information com- plexity and compare it with some ordinary information criteria.en_US
dc.language.isoengen_US
dc.relation.ispartofHacettepe Journal of Mathematics and Statisticsen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectMatematiken_US
dc.subjectİstatistik ve Olasılıken_US
dc.titleInformation complexity criterion for order determination in autoregressive modelsen_US
dc.typearticleen_US
dc.department. . .en_US
dc.institutionauthor. . .
dc.identifier.volume40en_US
dc.identifier.issue4en_US
dc.identifier.startpage601en_US
dc.identifier.endpage607en_US
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.wosWOS:000295555700013
dc.identifier.scopus2-s2.0-80053087167
dc.identifier.trdizinidTVRJeE5UVXdNQT09en_US
dc.identifier.trdizinid121550
dc.identifier.scopusqualityQ2
dc.indekslendigikaynakScopus
dc.indekslendigikaynakTR-Dizin


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