Package: fastcox 1.1.4
Yi Yang
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:10.4310/SII.2013.v6.n2.a1>.
Authors:
fastcox_1.1.4.tar.gz
fastcox_1.1.4.zip(r-4.7-x86_64)fastcox_1.1.4.zip(r-4.7-arm64)fastcox_1.1.4.zip(r-4.6-x86_64)fastcox_1.1.4.zip(r-4.6-arm64)
fastcox_1.1.4.tar.gz(r-4.7-arm64)fastcox_1.1.4.tar.gz(r-4.7-x86_64)fastcox_1.1.4.tar.gz(r-4.6-arm64)fastcox_1.1.4.tar.gz(r-4.6-x86_64)
fastcox_1.1.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
fastcox/json (API)
| # Install 'fastcox' in R: |
| install.packages('fastcox', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/archer-yang-lab/fastcox/issues
- FHT - FHT data introduced in Simon et al. (2011).
Last updated from:51b5367d0e. Checks:9 OK, 1 WARNING. Indexed: no.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 94 | ||
| linux-devel-x86_64 | OK | 113 | ||
| source / vignettes | OK | 178 | ||
| linux-release-arm64 | OK | 118 | ||
| linux-release-x86_64 | OK | 108 | ||
| windows-devel-arm64 | OK | 303 | ||
| windows-devel-x86_64 | OK | 149 | ||
| windows-release-arm64 | WARNING | 186 | ||
| windows-release-x86_64 | OK | 108 | ||
| wasm-release | OK | 86 |
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Lasso and elastic-net penalized Cox's regression in high dimensions models using the cocktail algorithm | fastcox-package |
| Fits the regularization paths for the elastic net penalized Cox's model | cocktail |
| Cross-validation for cocktail | cv.cocktail cv.survpath |
| FHT data introduced in Simon et al. (2011). | FHT |
| Plot coefficients from a "cocktail" object | plot.cocktail |
| plot the cross-validation curve produced by cv.cocktail | plot.cv.cocktail |
| make predictions from a "cocktail" object. | predict.cocktail predict.survpath |
| print a cocktail object | print.cocktail |