Mixed Frequency Structured AR Model Identification

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dc.contributor.authorZamani, Mohsen
dc.contributor.authorFelsenstein, Elisabeth
dc.contributor.authorAnderson, Brian
dc.contributor.authorDeistler, Manfred
dc.coverage.spatialZurich Switzerland
dc.date.accessioned2015-12-10T23:18:33Z
dc.date.createdJuly 17-19 2013
dc.date.issued2013
dc.date.updated2015-12-10T10:07:24Z
dc.description.abstractThis paper is concerned with identifiability of an underlying high frequency multivariate stable singular AR system from mixed frequency observations. Such problems arise for instance in economics when some variables are observed monthly whereas others ar
dc.identifier.isbn9783033039629
dc.identifier.urihttp://hdl.handle.net/1885/65682
dc.publisherConference Organising Committee
dc.relation.ispartofseries2013 12th European Control Conference, ECC 2013
dc.rightsAuthor/s retain copyrighten_AU
dc.source2013 European Control Conference, ECC 2013
dc.titleMixed Frequency Structured AR Model Identification
dc.typeConference paper
dcterms.accessRightsOpen Accessen_AU
local.bibliographicCitation.lastpage1933
local.bibliographicCitation.startpage1928
local.contributor.affiliationZamani, Mohsen, College of Engineering and Computer Science, ANU
local.contributor.affiliationFelsenstein, Elisabeth, Technical University of Vienna
local.contributor.affiliationAnderson, Brian, College of Engineering and Computer Science, ANU
local.contributor.affiliationDeistler, Manfred, Vienna University of Technology
local.contributor.authoruidZamani, Mohsen, u4750055
local.contributor.authoruidAnderson, Brian, u8104642
local.description.notesImported from ARIES
local.description.refereedYes
local.identifier.absfor090602 - Control Systems, Robotics and Automation
local.identifier.absseo910199 - Macroeconomics not elsewhere classified
local.identifier.ariespublicationu4334215xPUB1143
local.identifier.scopusID2-s2.0-84893306542
local.type.statusPublished Version

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