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dc.contributor.authorGatu, Cristian-
dc.contributor.authorKontoghiorghes, Erricos John-
dc.date.accessioned2013-01-30T13:33:20Zen
dc.date.accessioned2013-05-16T08:21:59Z-
dc.date.accessioned2015-12-02T09:28:35Z-
dc.date.available2013-01-30T13:33:20Zen
dc.date.available2013-05-16T08:21:59Z-
dc.date.available2015-12-02T09:28:35Z-
dc.date.issued2005-11-
dc.identifier.citationComputational Management Science, 2005, vol. 2, no. 4, pp. 253-278en_US
dc.identifier.issn16196988-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/2091-
dc.description.abstractAlgorithms for computing the subset Vector Autoregressive (VAR) models are proposed. These algorithms can be used to choose a subset of the most statistically-significant variables of a VAR model. In such cases, the selection criteria are based on the residual sum of squares or the estimated residual covariance matrix. The VAR model with zero coefficient restrictions is formulated as a Seemingly Unrelated Regressions (SUR) model. Furthermore, the SUR model is transformed into one of smaller size, where the exogenous matrices comprise columns of a triangular matrix. Efficient algorithms which exploit the common columns of the exogenous matrices, sparse structure of the variance-covariance of the disturbances and special properties of the SUR models are investigated. The main computational tool of the selection strategies is the generalized QR decomposition and its modificationen_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.relation.ispartofComputational Management Scienceen_US
dc.rights© Springer Natureen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.subjectLeast squaresen_US
dc.subjectAlgorithmsen_US
dc.subjectStrategyen_US
dc.titleEfficient strategies for deriving the subset var modelsen_US
dc.typeArticleen_US
dc.collaborationUniversité de Neuchâtelen_US
dc.journalsSubscriptionen_US
dc.countryGreeceen_US
dc.subject.fieldNatural Sciencesen_US
dc.publicationPeer Revieweden_US
dc.identifier.doi10.1007/s10287-004-0021-xen_US
dc.dept.handle123456789/54en
dc.relation.issue4en_US
dc.relation.volume2en_US
cut.common.academicyear2005-2006en_US
dc.identifier.spage253en_US
dc.identifier.epage278en_US
item.fulltextNo Fulltext-
item.languageiso639-1en-
item.grantfulltextnone-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.cerifentitytypePublications-
item.openairetypearticle-
crisitem.journal.journalissn1619-6988-
crisitem.journal.publisherSpringer Nature-
crisitem.author.deptDepartment of Finance, Accounting and Management Science-
crisitem.author.facultyFaculty of Tourism Management, Hospitality and Entrepreneurship-
crisitem.author.orcid0000-0001-9704-9510-
crisitem.author.parentorgFaculty of Management and Economics-
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