Penalized splines and reproducing kernel methods

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dc.contributor.author Pearce, N. en_US
dc.contributor.author Wand, Matt en_US
dc.contributor.editor en_US
dc.date.accessioned 2012-02-02T04:08:52Z
dc.date.available 2012-02-02T04:08:52Z
dc.date.issued 2006 en_US
dc.identifier 2010000457 en_US
dc.identifier.citation Pearce N. and Wand Matt 2006, 'Penalized splines and reproducing kernel methods', American Statistical Association, vol. 60, no. 3, pp. 233-240. en_US
dc.identifier.issn 0003-1305 en_US
dc.identifier.other C1UNSUBMIT en_US
dc.identifier.uri http://hdl.handle.net/10453/14492
dc.description.abstract Two data analytic research areas?penalized splines and reproducing kernel methods?have 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. en_US
dc.language en_US
dc.publisher American Statistical Association en_US
dc.relation.isbasedon http://dx.doi.org/10.1198/000313006X124541 en_US
dc.title Penalized splines and reproducing kernel methods en_US
dc.parent The American Statistician en_US
dc.journal.volume 60 en_US
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 010400 en_US
dc.personcode 0000064996 en_US
dc.personcode 110509 en_US
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 en_US
dc.staffid en_US
dc.staffid 110509 en_US


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