Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/58539
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dc.contributor.authorTeerawut Teetranonten_US
dc.contributor.authorWoraphon Yamakaen_US
dc.contributor.authorSongsak Sriboonchittaen_US
dc.date.accessioned2018-09-05T04:26:03Z-
dc.date.available2018-09-05T04:26:03Z-
dc.date.issued2018-01-01en_US
dc.identifier.issn1860949Xen_US
dc.identifier.other2-s2.0-85037821108en_US
dc.identifier.other10.1007/978-3-319-70942-0_43en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85037821108&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/58539-
dc.description.abstract© Springer International Publishing AG 2018. This paper employ VAR model to analyse and investigate the relationship among oil, gold, and rubber prices. A convex combination approach is proposed to obtain appropriate value of the interval data in VAR model. The construction of interval VAR model based on the convex combination method for the analysis of their forecast performance are also introduced and discussed via the simulation study, as well as comparing the performance with conventional center method. To illustrate the usefulness of the proposed model, an empirical application on a weekly sample of commodity price is provided. The results show the performance of our proposed model and also provide some relationship between commodity prices.en_US
dc.subjectComputer Scienceen_US
dc.titleGeneralize weighted in interval data for fitting a vector autoregressive modelen_US
dc.typeBook Seriesen_US
article.title.sourcetitleStudies in Computational Intelligenceen_US
article.volume753en_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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