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Modelling association between two irregularly observed spatio-temporal processes by using smoothed maximum covariance analysis

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dc.contributor.authorSalim, Agus
dc.contributor.authorPawitan, Yudi
dc.contributor.authorBond, K
dc.date.accessioned2015-12-13T22:48:48Z
dc.date.issued2005
dc.date.updated2015-12-11T10:30:52Z
dc.description.abstractClimatic phenomena such as the El-Niño-southern oscillation and the north Atlantic oscillation are results of complex interactions between atmospheric and oceanic processes. Understanding the interactions has enabled scientists to give early warning of t
dc.identifier.issn0035-9254
dc.identifier.urihttp://hdl.handle.net/1885/80235
dc.publisherBlackwell Publishing Ltd
dc.sourceJournal of the Royal Statistical Society Series C
dc.subjectKeywords: Canonical covariance; Climate changes; Incomplete data; Mixed models; Partial least squares; Smoothing
dc.titleModelling association between two irregularly observed spatio-temporal processes by using smoothed maximum covariance analysis
dc.typeJournal article
local.bibliographicCitation.issuePart 3
local.bibliographicCitation.lastpage573
local.bibliographicCitation.startpage555
local.contributor.affiliationSalim, Agus, College of Medicine, Biology and Environment, ANU
local.contributor.affiliationPawitan, Yudi, Karolinska Institutet
local.contributor.affiliationBond, K, University College Cork
local.contributor.authoruidSalim, Agus, u4163010
local.description.embargo2037-12-31
local.description.notesImported from ARIES
local.description.refereedYes
local.identifier.absfor010401 - Applied Statistics
local.identifier.absfor040605 - Palaeoclimatology
local.identifier.ariespublicationMigratedxPub8523
local.identifier.citationvolume54
local.identifier.doi10.1111/j.1467-9876.2005.05300.x
local.identifier.scopusID2-s2.0-18444418008
local.type.statusPublished Version

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