Variable selection methods in high-dimensional regression: a simulation study
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...
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| Outros Autores: | , |
| Formato: | article |
| Idioma: | eng |
| Publicado em: |
2015
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| Assuntos: | |
| Texto completo: | http://hdl.handle.net/1822/43688 |
| País: | Portugal |
| Oai: | oai:repositorium.sdum.uminho.pt:1822/43688 |