Package: tfCox 0.1.0

tfCox: Fits Piecewise Polynomial with Data-Adaptive Knots in Cox Model

In Cox's proportional hazard model, covariates are modeled as linear function and may not be flexible. This package implements additive trend filtering Cox proportional hazards model as proposed in Jiacheng Wu & Daniela Witten (2019) "Flexible and Interpretable Models for Survival Data", Journal of Computational and Graphical Statistics, <doi:10.1080/10618600.2019.1592758>. The fitted functions are piecewise polynomial with adaptively chosen knots.

Authors:Jiacheng Wu [aut, cre], Daniela Witten [aut], Taylor Arnold [ctb], Veeranjaneyulu Sadhanala [ctb], Ryan Tibshirani [ctb]

tfCox_0.1.0.tar.gz
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tfCox.pdf |tfCox.html
tfCox/json (API)

# Install 'tfCox' in R:
install.packages('tfCox', repos = c('https://wujiacheng.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

cpp

1.00 score 120 downloads 12 exports 4 dependencies

Last updated 6 years agofrom:2ee11a883a. Checks:12 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 29 2025
R-4.5-win-x86_64OKMar 29 2025
R-4.5-mac-x86_64OKMar 29 2025
R-4.5-mac-aarch64OKMar 29 2025
R-4.5-linux-x86_64OKMar 29 2025
R-4.4-win-x86_64OKMar 29 2025
R-4.4-mac-x86_64OKMar 29 2025
R-4.4-mac-aarch64OKMar 29 2025
R-4.4-linux-x86_64OKMar 29 2025
R-4.3-win-x86_64OKMar 29 2025
R-4.3-mac-x86_64OKMar 29 2025
R-4.3-mac-aarch64OKMar 29 2025

Exports:cv_tfCoxnegloglikplot.cv_tfCoxplot.sim_datplot.tfCoxpredict_best_lambdapredict.tfCoxsim_datsummary.cv_tfCoxsummary.tfCoxtfCoxtfCox_choose_lambda

Dependencies:latticeMatrixRcppsurvival