Package: FADA
Type: Package
Title: Variable selection for supervised classification in high
        dimension
Version: 1.1
Date: 2014-06-11
Author: Emeline Perthame (Agrocampus Ouest, Rennes, France), Chloe Friguet
    (Universite de Bretagne Sud, Vannes, France) and David Causeur (Agrocampus
    Ouest, Rennes, France)
Maintainer: David Causeur <david.causeur@agrocampus-ouest.fr>
Description: The functions provided in the FADA (Factor Adjusted Discriminant Analysis) package aim at performing
    supervised classification models and variable selection on dependent
    covariates. The classification procedures are combined with a factor
    modeling of dependence among covariates. The available procedures are Lasso
    regularized logistic model (see Friedman et al. (2010)), sparse linear
    discriminant analysis (see Clemmensen et al. (2011)), shrinkage linear and
    diagonal discriminant analysis (see M. Ahdesmaki et al. (2010)).
License: GPL (>= 2)
Depends: MASS, elasticnet
Imports: sparseLDA,sda,glmnet,mnormt
Packaged: 2014-08-28 14:33:08 UTC; Emeline
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2014-09-01 12:59:19
