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dc.contributor.author오만숙-
dc.contributor.author신동완-
dc.date.accessioned2016-08-28T11:08:59Z-
dc.date.available2016-08-28T11:08:59Z-
dc.date.issued2005-
dc.identifier.issn0266-4763-
dc.identifier.otherOAK-3042-
dc.identifier.urihttps://dspace.ewha.ac.kr/handle/2015.oak/219643-
dc.description.abstractBayesian analysis of panel data using a class of momentum threshold autoregressive (MTAR) models is considered. Posterior estimation of parameters of the MTAR models is done by using a simple Markov Chain Monte Carlo (MCMC) algorithm. Selection of appropriate differenced variables, test for asymmetry and unit roots are recast as model selections and a simple way of computing posterior probabilities of the candidate models is proposed. The proposed method is applied to the yearly unemployment rates of 51 US states and the results show strong evidence of stationarity and asymmetry. © 2005 Taylor & Francis.-
dc.languageEnglish-
dc.titleBayesian analysis of panel data using an MTAR model-
dc.typeArticle-
dc.relation.issue8-
dc.relation.volume32-
dc.relation.indexSCIE-
dc.relation.indexSCOPUS-
dc.relation.startpage841-
dc.relation.lastpage854-
dc.relation.journaltitleJournal of Applied Statistics-
dc.identifier.doi10.1007/s00170-003-1931-4-
dc.identifier.wosidWOS:000233659200006-
dc.identifier.scopusid2-s2.0-31144432865-
dc.author.googleJung Y.Y.-
dc.author.googleShin D.W.-
dc.author.googleOh M.-S.-
dc.contributor.scopusid오만숙(7201600334)-
dc.contributor.scopusid신동완(7403352539)-
dc.date.modifydate20170601134935-
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자연과학대학 > 통계학전공 > Journal papers
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