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dc.contributor.authorEilers, Paul H.C.
dc.contributor.authorMarx, Brian D.
dc.contributor.authorDurbán, Maria
dc.date.accessioned2016-07-05T15:21:40Z
dc.date.available2016-07-05T15:21:40Z
dc.date.issued2015-12
dc.identifier.citationEilers, Paul H.C.; Marx, Brian D.; Durbán, Maria. Twenty years of P-splines. "SORT", Desembre 2015, vol. 39, núm. 2, p. 149-186.
dc.identifier.issn1696-2281
dc.identifier.urihttp://hdl.handle.net/2117/88526
dc.description.abstractP-splines first appeared in the limelight twenty years ago. Since then they have become popular in applications and in theoretical work. The combination of a rich B-spline basis and a simple difference penalty lends itself well to a variety of generalizations, because it is based on regression. In effect, P-splines allow the building of a “backbone” for the “mixing and matching” of a variety of additive smooth structure components, while inviting all sorts of extensions: varying-coefficient effects, signal (functional) regressors, two-dimensional surfaces, non-normal responses, quantile (expectile) modelling, among others. Strong connections with mixed models and Bayesian analysis have been established. We give an overview of many of the central developments during the first two decades of P-splines.
dc.format.extent38 p.
dc.language.isoeng
dc.publisherInstitut d'Estadística de Catalunya
dc.relation.ispartofSORT. 2015, Vol. 39, Núm. 2
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica
dc.subject.otherB-splines
dc.subject.otherpenalty
dc.subject.otheradditive model
dc.subject.othermixed model
dc.subject.othermultidimensional smoothing
dc.titleTwenty years of P-splines
dc.typeArticle
dc.description.peerreviewedPeer Reviewed
dc.subject.amsClassificació AMS::41 Approximations and expansions
dc.subject.amsClassificació AMS::62 Statistics::62G Nonparametric inference
dc.subject.amsClassificació AMS::62 Statistics::62J Linear inference, regression
dc.rights.accessOpen Access
local.citation.publicationNameSORT
local.citation.volume39
local.citation.number2
local.citation.startingPage149
local.citation.endingPage186


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