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>.
|Author||Aurelie Gueudin [aut, cre], Anne Gegout-Petit [aut]|
|Maintainer||Aurelie Gueudin <[email protected]>|
|Package repository||View on CRAN|
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