Handle URI:
http://hdl.handle.net/10754/597009
Title:
Semiparametric regression during 2003–2007
Authors:
Ruppert, David; Wand, M.P.; Carroll, Raymond J.
Abstract:
Semiparametric regression is a fusion between parametric regression and nonparametric regression that integrates low-rank penalized splines, mixed model and hierarchical Bayesian methodology – thus allowing more streamlined handling of longitudinal and spatial correlation. We review progress in the field over the five-year period between 2003 and 2007. We find semiparametric regression to be a vibrant field with substantial involvement and activity, continual enhancement and widespread application.
Citation:
Ruppert D, Wand MP, Carroll RJ (2009) Semiparametric regression during 2003–2007. Electronic Journal of Statistics 3: 1193–1256. Available: http://dx.doi.org/10.1214/09-ejs525.
Publisher:
Institute of Mathematical Statistics
Journal:
Electronic Journal of Statistics
KAUST Grant Number:
KUS-CI-016-04
Issue Date:
2009
DOI:
10.1214/09-ejs525
PubMed ID:
20305800
Type:
Article
ISSN:
1935-7524
Sponsors:
Supported by grants from the National Cancer Institute (CA57030) and the National Science Foundation (DMS-0805975). Supported by a grant from the Australian Research Council (DP0877055). Supported by grants from the National Cancer Institute (CA57030, CA104620), and also in part by award number KUS-CI-016-04 made by the King Abdullah University of Science and Technology.
Appears in Collections:
Publications Acknowledging KAUST Support

Full metadata record

DC FieldValue Language
dc.contributor.authorRuppert, Daviden
dc.contributor.authorWand, M.P.en
dc.contributor.authorCarroll, Raymond J.en
dc.date.accessioned2016-02-23T13:52:23Zen
dc.date.available2016-02-23T13:52:23Zen
dc.date.issued2009en
dc.identifier.citationRuppert D, Wand MP, Carroll RJ (2009) Semiparametric regression during 2003–2007. Electronic Journal of Statistics 3: 1193–1256. Available: http://dx.doi.org/10.1214/09-ejs525.en
dc.identifier.issn1935-7524en
dc.identifier.pmid20305800en
dc.identifier.doi10.1214/09-ejs525en
dc.identifier.urihttp://hdl.handle.net/10754/597009en
dc.description.abstractSemiparametric regression is a fusion between parametric regression and nonparametric regression that integrates low-rank penalized splines, mixed model and hierarchical Bayesian methodology – thus allowing more streamlined handling of longitudinal and spatial correlation. We review progress in the field over the five-year period between 2003 and 2007. We find semiparametric regression to be a vibrant field with substantial involvement and activity, continual enhancement and widespread application.en
dc.description.sponsorshipSupported by grants from the National Cancer Institute (CA57030) and the National Science Foundation (DMS-0805975). Supported by a grant from the Australian Research Council (DP0877055). Supported by grants from the National Cancer Institute (CA57030, CA104620), and also in part by award number KUS-CI-016-04 made by the King Abdullah University of Science and Technology.en
dc.publisherInstitute of Mathematical Statisticsen
dc.rightsCreative Commons Attribution License.en
dc.rights.urihttp://creativecommons.org/licenses/by/2.5/legalcodeen
dc.titleSemiparametric regression during 2003–2007en
dc.typeArticleen
dc.identifier.journalElectronic Journal of Statisticsen
dc.contributor.institutionSchool of Operations Research and Information Engineering, Cornell University, 1170 Comstock Hall, Ithaca, NY 14853, U.S.A.en
dc.contributor.institutionCentre for Statistical and Survey Methodology, School of Mathematics and Applied Statistics, University of Wollongong, Wollongong 2522, Australiaen
kaust.grant.numberKUS-CI-016-04en

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