AdapEnetClass: A Class of Adaptive Elastic-net Methods for Censored Data

Provides new approaches to variable selection for censored data including its high-dimensionality, based on AFT models optimized using regularized weighted least squares. Approaches 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 are provided with both simulated and real (MCL) data examples.

Version: 1.1
Depends: imputeYn, glmnet, lars, quadprog, R (≥ 3.0.2)
Published: 2014-10-19
Author: Hasinur Rahaman Khan and Ewart Shaw
Maintainer: Hasinur Rahaman Khan <hasinurkhan at gmail.com>
License: GPL-2
NeedsCompilation: no
In views: Survival
CRAN checks: AdapEnetClass results

Downloads:

Reference manual: AdapEnetClass.pdf
Package source: AdapEnetClass_1.1.tar.gz
Windows binaries: r-devel: AdapEnetClass_1.1.zip, r-release: AdapEnetClass_1.1.zip, r-oldrel: AdapEnetClass_1.1.zip
OS X Snow Leopard binaries: r-release: AdapEnetClass_1.1.tgz, r-oldrel: AdapEnetClass_1.1.tgz
OS X Mavericks binaries: r-release: AdapEnetClass_1.1.tgz
Old sources: AdapEnetClass archive