armada: A Statistical Methodology to Select Covariates in
High-Dimensional Data under Dependence
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>.
| Version: |
0.1.0 |
| Imports: |
stats, mvtnorm, ClustOfVar, FAMT, graphics, VSURF, glmnet, anapuce, qvalue, parallel, doParallel, impute, ComplexHeatmap, circlize |
| Published: |
2019-04-04 |
| Author: |
Aurelie Gueudin [aut, cre],
Anne Gegout-Petit [aut] |
| Maintainer: |
Aurelie Gueudin <aurelie.gueudin at univ-lorraine.fr> |
| License: |
GPL-3 |
| NeedsCompilation: |
no |
| CRAN checks: |
armada results |
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