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]>

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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:

2.71 score 17 scripts 480 downloads 3 mentions 4 exports 2 dependencies

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

TargetResultDate
Doc / VignettesOKNov 04 2024
R-4.5-win-x86_64OKNov 04 2024
R-4.5-linux-x86_64OKNov 04 2024
R-4.4-win-x86_64OKNov 04 2024
R-4.4-mac-x86_64OKNov 04 2024
R-4.4-mac-aarch64OKNov 04 2024
R-4.3-win-x86_64OKNov 04 2024
R-4.3-mac-x86_64OKNov 04 2024
R-4.3-mac-aarch64OKNov 04 2024

Exports:cocktailcv.cocktailcv.survpathpredict.cocktail

Dependencies:latticeMatrix