Penalized splines and reproducing kernel methods

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dc.contributor.author Pearce, ND
dc.contributor.author Wand, M
dc.date.accessioned 2012-02-02T04:08:52Z
dc.date.issued 2006-01
dc.identifier.citation The American Statistician, 2006, 60 (3), pp. 233 - 240
dc.identifier.issn 0003-1305
dc.identifier.other C1UNSUBMIT en_US
dc.identifier.uri http://hdl.handle.net/10453/14492
dc.description.abstract Two data analytic research areaspenalized splines and reproducing kernel methodshave become very vibrant since the mid-1990s. This article shows how the former can be embedded in the latter via theory for reproducing kernel Hilbert spaces. This connection facilitates cross-fertilization between the two bodies of research. In particular, connections between support vector machines and penalized splines are established. These allow for significant reductions in computational complexity, and easier incorporation of special structure such as additivity.
dc.publisher American Statistical Association
dc.relation.isbasedon 10.1198/000313006X124541
dc.title Penalized splines and reproducing kernel methods
dc.type Journal Article
dc.parent The American Statistician
dc.journal.volume 3
dc.journal.volume 60
dc.journal.number 3 en_US
dc.publocation United States en_US
dc.identifier.startpage 233 en_US
dc.identifier.endpage 240 en_US
dc.cauo.name SCI.Mathematical Sciences en_US
dc.conference Verified OK en_US
dc.for 0104 Statistics
dc.personcode 110509
dc.percentage 100 en_US
dc.classification.name Statistics en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom en_US
dc.date.activity en_US
dc.location.activity en_US
dc.description.keywords NA
pubs.embargo.period Not known
pubs.organisational-group /University of Technology Sydney
pubs.organisational-group /University of Technology Sydney/Faculty of Science
utslib.copyright.status Closed Access
utslib.copyright.date 2015-04-15 12:17:09.805752+10
pubs.consider-herdc false
utslib.collection.history School of Mathematical Sciences (ID: 340)
utslib.collection.history Closed (ID: 3)


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