cocktail-package: Lasso and elastic-net penalized Cox's regression in high...

In fastcox: Lasso and Elastic-Net Penalized Cox's Regression in High Dimensions Models using the Cocktail Algorithm

Lasso and elastic-net penalized Cox's regression in high dimensions models using the cocktail algorithm

Description

We introduce a cocktail algorithm, a good mixture of coordinate decent, the majorization-minimization principle and the strong rule, for computing the solution paths of the elastic net penalized Cox's proportional hazards model.

Details

Package:	fastcox
Type:	Package
Version:	1.0.0
Date:	2012-03-26
Depends:	Matrix
License:	GPL (version 2)
URL:	https://github.com/archer-yang-lab/fastcox

Author(s)

Yi Yang and Hui Zou
Maintainer: Yi Yang <[e-mail]>

References

Yang, Y. and Zou, H. (2013), "A Cocktail Algorithm for Solving The Elastic Net Penalized Cox's Regression in High Dimensions", Statistics and Its Interface, 6:2, 167-173.
https://github.com/archer-yang-lab/fastcox

Examples

data(FHT)
m1<-cocktail(x=FHT$x,y=FHT$y,d=FHT$status,alpha=0.5)
predict(m1,type="nonzero")
plot(m1)

fastcox documentation built on June 8, 2025, 10:47 a.m.