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dc.contributor.authorParavee Maneejuken_US
dc.contributor.authorWoraphon Yamakaen_US
dc.contributor.authorSongsak Sriboonchittaen_US
dc.date.accessioned2018-09-05T04:26:15Z-
dc.date.available2018-09-05T04:26:15Z-
dc.date.issued2018-01-01en_US
dc.identifier.issn16113349en_US
dc.identifier.issn03029743en_US
dc.identifier.other2-s2.0-85043980870en_US
dc.identifier.other10.1007/978-3-319-75429-1_26en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85043980870&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/58560-
dc.description.abstract© 2018, Springer International Publishing AG, part of Springer Nature. This study proposes the mixture Markov-switching autoregressive model, which allows variation in error distribution across different regimes. This model is generalized from the ordinary MS-AR model owing to two considerations, but related to each other. First, we have concern about the mixture of distributions or populations, which often prevails in economic time series. Second, when using the MS models to analyse economic fluctuation, we doubt if each regime in the model can have distinct distribution. All of these concerns are addressed by an empirical study.en_US
dc.subjectComputer Scienceen_US
dc.subjectMathematicsen_US
dc.titleA Markov-Switching Model with Mixture Distribution Regimesen_US
dc.typeBook Seriesen_US
article.title.sourcetitleLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)en_US
article.volume10758 LNAIen_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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