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dc.contributor.author소병수-
dc.date.accessioned2016-08-28T11:08:27Z-
dc.date.available2016-08-28T11:08:27Z-
dc.date.issued2003-
dc.identifier.issn0167-7152-
dc.identifier.otherOAK-1613-
dc.identifier.urihttps://dspace.ewha.ac.kr/handle/2015.oak/219291-
dc.description.abstractOn the basis of simple algebraic identities, we derive a new updating formula for the maximized log-likelihoods. This formula enables us to decompose the predictive minimum description length (PMDL) criterion of Rissanen J. Roy. Statist. Soc. Ser. B 49 (1987) 1 into maximized log-likelihood and a penalty term representing model complexity. Statistical implications for model selection problems are discussed. © 2003 Elsevier B.V. All rights reserved.-
dc.languageEnglish-
dc.titleMaximized log-likelihood updating and model selection-
dc.typeArticle-
dc.relation.issue3-
dc.relation.volume64-
dc.relation.indexSCIE-
dc.relation.indexSCOPUS-
dc.relation.startpage293-
dc.relation.lastpage303-
dc.relation.journaltitleStatistics and Probability Letters-
dc.identifier.doi10.1016/S0167-7152(03)00174-3-
dc.identifier.wosidWOS:000185300800010-
dc.identifier.scopusid2-s2.0-0042929711-
dc.author.googleSo B.S.-
dc.contributor.scopusid소병수(7005199584)-
dc.date.modifydate20211102105704-
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자연과학대학 > 통계학전공 > Journal papers
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