netcox: Structural Learning in Cox Models with Time-Dependent Covariates

Efficient procedures for fitting and cross-validating the overlapping group Lasso (implemented in C++) for Cox models with time-dependent covariates. The penalty term is a weighted sum of infinity norms of (overlapping) groups of coefficients, which can select variables structurally with a specific grouping structure.

Version: 1.0.1
Depends: R (≥ 3.5.0), survival, glmnet
Imports: Rcpp (≥ 1.0.10)
LinkingTo: Rcpp
Suggests: testthat (≥ 3.0.0)
Published: 2023-02-27
DOI: 10.32614/CRAN.package.netcox
Author: Yi Lian [aut, cre], Guanbo Wang [aut], Archer Y. Yang [aut], Julien Mairal [ctb]
Maintainer: Yi Lian <yi.lian at>
License: GPL (≥ 3)
Copyright: file inst/COPYRIGHTS
netcox copyright details
NeedsCompilation: yes
Materials: README
CRAN checks: netcox results


Reference manual: netcox.pdf


Package source: netcox_1.0.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): netcox_1.0.1.tgz, r-oldrel (arm64): netcox_1.0.1.tgz, r-release (x86_64): netcox_1.0.1.tgz, r-oldrel (x86_64): netcox_1.0.1.tgz
Old sources: netcox archive


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