CRAN/E | netcox

netcox

Structural Learning in Cox Models with Time-Dependent Covariates

Installation

About

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.

Copyright file inst/COPYRIGHTS netcox copyright details

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Version 1.0.1
R ≥ 3.5.0
Published 2023-02-27 426 days ago
Needs compilation? yes
License GPL (≥ 3)
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Maintainer

Maintainer

Yi Lian

yi.lian@mail.mcgill.ca

Authors

Yi Lian

aut / cre

Guanbo Wang

aut

Archer Y. Yang

aut

Julien Mairal

ctb

Material

README
Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

netcox archive

Depends

R ≥ 3.5.0
survival
glmnet

Imports

Rcpp ≥ 1.0.10

Suggests

testthat ≥ 3.0.0

LinkingTo

Rcpp