Two steps variable selection procedure in a context of high-dimensional dependent data but few observations. First step is dedicated to eliminate dependence between variables (clustering of variables, followed by factor analysis inside each cluster). Second step is a variable selection using by aggregation of adapted methods. Bastien B., Chakir H., Gegout-Petit A., Muller-Gueudin A., Shi Y. A statistical methodology to select covariates in high-dimensional data under dependence. Application to the classification of genetic profiles associated with outcome of a non-small-cell lung cancer treatment. 2018. <https://hal.archives-ouvertes.fr/hal-01939694>.
Package details |
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Author | Aurelie Gueudin [aut, cre], Anne Gegout-Petit [aut] |
Maintainer | Aurelie Gueudin <aurelie.gueudin@univ-lorraine.fr> |
License | GPL-3 |
Version | 0.1.0 |
Package repository | View on CRAN |
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