Package: fastcox 1.1.3

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

We implement 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. The package is an implementation of Yang, Y. and Zou, H. (2013) DOI: <doi:10.4310/SII.2013.v6.n2.a1>.

Authors:Yi Yang <[email protected]>, Hui Zou <[email protected]>

fastcox_1.1.3.tar.gz
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fastcox.pdf |fastcox.html
fastcox/json (API)

# Install 'fastcox' in R:
install.packages('fastcox', repos = c('https://archer-yang-lab.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/emeryyi/fastcox/issues

Uses libs:
  • fortran– Runtime library for GNU Fortran applications
Datasets:
  • FHT - FHT data introduced in Simon et al. (2011).

On CRAN:

fortran

2.71 score 17 scripts 476 downloads 3 mentions 4 exports 2 dependencies

Last updated 7 years agofrom:2560941353. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKJan 03 2025
R-4.5-win-x86_64OKJan 03 2025
R-4.5-linux-x86_64OKJan 03 2025
R-4.4-win-x86_64OKJan 03 2025
R-4.4-mac-x86_64OKJan 03 2025
R-4.4-mac-aarch64OKJan 03 2025
R-4.3-win-x86_64OKJan 03 2025
R-4.3-mac-x86_64OKJan 03 2025
R-4.3-mac-aarch64OKJan 03 2025

Exports:cocktailcv.cocktailcv.survpathpredict.cocktail

Dependencies:latticeMatrix