AdapEnetClass: A class of adaptive elastic net methods for censored data

The package provides new approaches to variable selection for censored data, based on AFT models optimized using regularized weighted least squares. Namely, a weighted elastic net, an adaptive elastic net, and two of their extensions by adding censoring observations as constraints into their model optimization frameworks.

Version: 1.0
Depends: imputeYn, glmnet, lars, R (≥ 2.14.2)
Published: 2013-11-10
Author: Hasinur Rahaman Khan and Ewart Shaw
Maintainer: Hasinur Rahaman Khan <hasinurkhan at>
License: GPL-2
NeedsCompilation: no
In views: Survival
CRAN checks: AdapEnetClass results


Reference manual: AdapEnetClass.pdf
Package source: AdapEnetClass_1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X Snow Leopard binaries: r-release: AdapEnetClass_1.0.tgz, r-oldrel: AdapEnetClass_1.0.tgz
OS X Mavericks binaries: r-release: AdapEnetClass_1.0.tgz