enetLTS: Robust and Sparse Methods for High Dimensional Linear and Logistic Regression

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.

Package details

AuthorFatma Sevinc KURNAZ and Irene HOFFMANN and Peter FILZMOSER
MaintainerFatma Sevinc Kurnaz <[email protected]>
LicenseGPL (>= 3)
Version0.1.0
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("enetLTS")

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enetLTS documentation built on May 1, 2019, 7:43 p.m.