Package: RAEN
Title: Random Approximate Elastic Net (RAEN) Variable Selection Method
Version: 0.2
Encoding: UTF-8
Description: The Proportional Subdistribution Hazard (PSH) model has been popular for estimating the effects of the covariates on the cause of interest in Competing Risks analysis. The fast accumulation of large scale datasets has posed a challenge to classical statistical methods. Current penalized variable selection methods show unsatisfactory performance in ultra-high dimensional data. We propose a novel method, the Random Approximate Elastic Net (RAEN), with a robust and generalized solution to the variable selection problem for the PSH model. Our method shows improved sensitivity for variable selection compared with current methods.
Author: Han Sun and Xiaofeng Wang
Maintainer: Han Sun <han.sunny@gmail.com>
URL: https://github.com/saintland/RAEN
Imports: boot, foreach, doParallel,glmnet, fastcmprsk
Depends: R(>= 3.5.0), lars
Suggests: testthat, knitr, rmarkdown
License: GPL (>= 2)
RoxygenNote: 7.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-02-21 04:58:10 UTC; sunh
Repository: CRAN
Date/Publication: 2021-02-21 06:00:16 UTC
Built: R 4.0.5; ; 2022-04-21 09:44:02 UTC; windows
