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Identifying secondary series for stepwise common singular spectrum analysis

dc.contributor.authorViljoen, H.en_ZA
dc.contributor.authorSteel, S. J.en_ZA
dc.date.accessioned2018-01-10T07:59:09Z
dc.date.available2018-01-10T07:59:09Z
dc.date.issued2013
dc.identifier.citationViljoen, H. & Steel, S. J. 2013. Identifying secondary series for stepwise common singular spectrum analysis. Orion, 29(2):155–167, doi:10.5784/29-2-134.
dc.identifier.issn2224-0004 (online)
dc.identifier.issn0259-191X (print)
dc.identifier.otherdoi:10.5784/29-2-134
dc.identifier.urihttp://hdl.handle.net/10019.1/103032
dc.descriptionCITATION: Viljoen, H. & Steel, S. J. 2013. Identifying secondary series for stepwise common singular spectrum analysis. Orion, 29(2):155–167, doi:10.5784/29-2-134.
dc.descriptionThe original publication is available at http://orion.journals.ac.za
dc.description.abstractCommon singular spectrum analysis is a technique which can be used to forecast a primary time series by using the information from a secondary series. Not all secondary series, however, provide useful information. A first contribution in this paper is to point out the properties which a secondary series should have in order to improve the forecast accuracy of the primary series. The second contribution is a proposal which can be used to select a secondary series from several candidate series. Empirical studies suggest that the proposal performs well.en_ZA
dc.description.urihttp://orion.journals.ac.za/pub/article/view/134
dc.format.extent13 pages
dc.language.isoen_ZAen_ZA
dc.publisherOperations Research Society of South Africa
dc.subjecttime series selectionen_ZA
dc.titleIdentifying secondary series for stepwise common singular spectrum analysisen_ZA
dc.typeArticleen_ZA
dc.description.versionPublisher's version
dc.rights.holderAuthors retain copyright


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