Package: enetLTS
Type: Package
Title: Robust and Sparse Methods for High Dimensional Linear and
        Logistic Regression
Version: 0.1.0
Date: 2018-01-18
Author: Fatma Sevinc KURNAZ and Irene HOFFMANN and Peter FILZMOSER
Maintainer: Fatma Sevinc Kurnaz <fatmasevinckurnaz@gmail.com>
Description: Fully robust versions of the elastic net estimator are introduced for linear and logistic regression, in particular high dimensional data by Kurnaz, Hoffmann and Filzmoser (2017) <DOI:10.1016/j.chemolab.2017.11.017>. The algorithm searches for outlier free subsets on which the classical elastic net estimators can be applied. 
License: GPL (>= 3)
Imports: ggplot2, glmnet, robustHD, grid, reshape, parallel, cvTools,
        stats
NeedsCompilation: no
Packaged: 2018-01-19 20:21:04 UTC; fatmasevinckurnaz
Repository: CRAN
Date/Publication: 2018-01-22 09:31:45 UTC
