Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/43688
Título: | Variable selection methods in high-dimensional regression: a simulation study |
Autor(es): | Shahriari, Shirin Faria, Susana Gonçalves, A. Manuela |
Palavras-chave: | High-dimensional data Partial least-squares regression Principle component regression Variable selection Bootstrap |
Data: | 2015 |
Editora: | Taylor and Francis |
Revista: | Communications in Statistics - Simulation and Computation |
Resumo(s): | 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. |
Tipo: | Artigo |
URI: | https://hdl.handle.net/1822/43688 |
DOI: | 10.1080/03610918.2013.833231 |
ISSN: | 0361-0918 1532-4141 |
Versão da editora: | http://www.tandfonline.com/doi/pdf/10.1080/03610918.2013.833231?needAccess=true |
Arbitragem científica: | yes |
Acesso: | Acesso restrito UMinho |
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 |