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dc.contributor.author오만숙*
dc.contributor.author신동완*
dc.date.accessioned2016-08-28T11:08:39Z-
dc.date.available2016-08-28T11:08:39Z-
dc.date.issued2002*
dc.identifier.issn0165-1765*
dc.identifier.otherOAK-12598*
dc.identifier.urihttps://dspace.ewha.ac.kr/handle/2015.oak/228696-
dc.description.abstractA new kernel for estimating long-run variances of stationary seasonal time series is proposed. The proposed kernel has an oscillating pattern which is in harmony with that of the autocovariance functions of seasonal time series. A Monte-Carlo experiment shows that the estimator based on the proposed kernel outperforms estimators based on existing kernels such as the Bartlett kernel, Parzen kernel, and Turkey-Hanning kernel for two typical monthly time series processes with moderate autocorrelations. © 2002 Elsevier Science B.V. All rights reserved.*
dc.languageEnglish*
dc.titleA new kernel for long-run variance estimates in seasonal time series models*
dc.typeArticle*
dc.relation.issue2*
dc.relation.volume76*
dc.relation.indexSSCI*
dc.relation.indexSCOPUS*
dc.relation.startpage165*
dc.relation.lastpage171*
dc.relation.journaltitleEconomics Letters*
dc.identifier.doi10.1016/S0165-1765(02)00048-4*
dc.identifier.scopusid2-s2.0-0035997443*
dc.author.googleShin D.W.*
dc.author.googleOh M.-S.*
dc.contributor.scopusid오만숙(7201600334)*
dc.contributor.scopusid신동완(7403352539)*
dc.date.modifydate20240116115756*
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자연과학대학 > 통계학전공 > Journal papers
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