Package: coxdev 0.4.0

Jonathan Taylor

coxdev: Cox Model Deviance, Gradient, Information and Score Sampling

Fast computation of the deviance of the Cox proportional hazards model (Cox (1972) <doi:10.1111/j.2517-6161.1972.tb00899.x>), its gradient and the diagonal of its Hessian with respect to the linear predictor, the information and its derivative in a direction as matrix-free linear operators, and draws of the score (multinomial, Bernoulli, Fisher noncentral hypergeometric or wild), with the ties of Breslow (1974) <doi:10.2307/2529620> or Efron (1977) <doi:10.1080/01621459.1977.10480613>, start times (left truncation), strata and sample weights. The 'C++' code is header-only, shared with the 'Python' package 'coxdev', and installed for packages that use it through 'LinkingTo'.

Authors:Jonathan Taylor [aut, cre], Trevor Hastie [aut], Balasubramanian Narasimhan [aut]

coxdev_0.4.0.tar.gz
coxdev_0.4.0.zip(r-4.7-x86_64)coxdev_0.4.0.zip(r-4.7-arm64)coxdev_0.4.0.zip(r-4.6-x86_64)coxdev_0.4.0.zip(r-4.6-arm64)
coxdev_0.4.0.tar.gz(r-4.7-arm64)coxdev_0.4.0.tar.gz(r-4.7-x86_64)coxdev_0.4.0.tar.gz(r-4.6-arm64)coxdev_0.4.0.tar.gz(r-4.6-x86_64)
coxdev_0.4.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
coxdev/json (API)

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

Bug tracker:https://github.com/jonathan-taylor/coxdev/issues

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

cpp

2.30 score 7 scripts 4 exports 3 dependencies

Last updated from:ec20f6ef07. Checks:10 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK125
linux-devel-x86_64OK132
source / vignettesOK235
linux-release-arm64OK117
linux-release-x86_64OK141
windows-devel-arm64OK231
windows-devel-x86_64OK205
windows-release-arm64OK227
windows-release-x86_64OK140
wasm-releaseOK109

Exports:CoxDevianceCoxInformationCoxInformationDerivativemake_cox_deviance

Dependencies:R6RcppRcppEigen

Sampling the score
A survival response | The methods | Choosing the multipliers | Reproducibility

Last update: 2026-11-07
Started: 2026-11-07

Using coxdev
A survival response | Deviance, gradient and information | Robust standard errors and the baseline hazard | What keeping state saves

Last update: 2026-11-07
Started: 2026-11-07