Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/43688
Registo completo
Campo DC | Valor | Idioma |
---|---|---|
dc.contributor.author | Shahriari, Shirin | por |
dc.contributor.author | Faria, Susana | por |
dc.contributor.author | Gonçalves, A. Manuela | por |
dc.date.accessioned | 2016-12-22T17:09:27Z | - |
dc.date.issued | 2015 | - |
dc.date.submitted | 2013 | - |
dc.identifier.issn | 0361-0918 | por |
dc.identifier.issn | 1532-4141 | por |
dc.identifier.uri | https://hdl.handle.net/1822/43688 | - |
dc.description.abstract | A challenging problem in the analysis of high-dimensional data is variable selection. In this study, we describe a bootstrap based technique for selecting predictors in partial least-squares regression (PLSR) and principle component regression (PCR) in high-dimensional data. Using a bootstrap-based technique for significance tests of the regression coefficients, a subset of the original variables can be selected to be included in the regression, thus obtaining a more parsimonious model with smaller prediction errors. We compare the bootstrap approach with several variable selection approaches (jack-knife and sparse formulation-based methods) on PCR and PLSR in simulation and real data. | por |
dc.description.sponsorship | This research was financed by FEDER Funds through “Programa Operacional Factores de Competitividade-COMPETE” and by Portuguese Funds through FCT—“Fundação para a Ciência e a Tecnologia”, within the Project Est-C/MAT/UI0013/2011.The author Shirin Shahriari has a Ph.D. scholarship by FCT SFRH/BD/51164/2010. | por |
dc.language.iso | eng | por |
dc.publisher | Taylor and Francis | por |
dc.relation | SFRH/BD/51164/2010. | por |
dc.rights | restrictedAccess | por |
dc.subject | High-dimensional data | por |
dc.subject | Partial least-squares regression | por |
dc.subject | Principle component regression | por |
dc.subject | Variable selection | por |
dc.subject | Bootstrap | por |
dc.title | Variable selection methods in high-dimensional regression: a simulation study | por |
dc.type | article | por |
dc.peerreviewed | yes | por |
dc.relation.publisherversion | http://www.tandfonline.com/doi/pdf/10.1080/03610918.2013.833231?needAccess=true | por |
sdum.publicationstatus | info:eu-repo/semantics/publishedVersion | por |
oaire.citationStartPage | 2548 | por |
oaire.citationEndPage | 2561 | por |
oaire.citationIssue | 10 | por |
oaire.citationTitle | Communications in Statistics - Simulation and Computation | por |
oaire.citationVolume | 44 | por |
dc.identifier.doi | 10.1080/03610918.2013.833231 | por |
dc.subject.fos | Ciências Naturais::Outras Ciências Naturais | por |
dc.subject.fos | Ciências Naturais::Matemáticas | por |
dc.subject.wos | Science & Technology | por |
sdum.journal | Communications in Statistics - Simulation and Computation | por |
Aparece nas coleções: | CMAT - Artigos em revistas com arbitragem / Papers in peer review journals |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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Shirin_Variable Selection_Manuscript.pdf Acesso restrito! | 680,4 kB | Adobe PDF | Ver/Abrir | |
Shirin_Variable Seelction_Tables.pdf Acesso restrito! | 98,39 kB | Adobe PDF | Ver/Abrir |