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dc.contributor.author신동완*
dc.date.accessioned2016-08-28T11:08:23Z-
dc.date.available2016-08-28T11:08:23Z-
dc.date.issued2000*
dc.identifier.issn0167-7152*
dc.identifier.otherOAK-367*
dc.identifier.urihttps://dspace.ewha.ac.kr/handle/2015.oak/218606-
dc.description.abstractFor polynomial regression models with spatially correlated errors, the covariance matrix of the ordinary least-squares estimator (OLSE) is shown to have the same limiting value as that of the generalized least-squares estimator (GLSE) under the same normalization. This implies that the OLSE is asymptotically efficient. © 2000 Elsevier Science B.V.*
dc.languageEnglish*
dc.titleAsymptotic efficiency of the OLSE for polynomial regression models with spatially correlated errors*
dc.typeArticle*
dc.relation.issue1*
dc.relation.volume47*
dc.relation.indexSCIE*
dc.relation.indexSCOPUS*
dc.relation.startpage1*
dc.relation.lastpage10*
dc.relation.journaltitleStatistics and Probability Letters*
dc.identifier.wosidWOS:000085184000001*
dc.identifier.scopusid2-s2.0-0002478823*
dc.author.googleShin D.W.*
dc.author.googleSong S.H.*
dc.contributor.scopusid신동완(7403352539)*
dc.date.modifydate20240116115756*
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자연과학대학 > 통계학전공 > Journal papers
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