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GPTCM: Generalized Promotion Time Cure Model with Bayesian Shrinkage Priors

Generalized promotion time cure model (GPTCM) via Bayesian hierarchical modeling for multiscale data integration (Zhao et al. (2025) <doi:10.48550/arXiv.2509.01001>). The Bayesian GPTCMs are applicable for both low- and high-dimensional data.

Version: 1.1.1
Depends: R (≥ 4.1.0)
Imports: Rcpp, survival, riskRegression, ggplot2, ggridges, miCoPTCM, loo, mvnfast, Matrix, scales, utils, stats, graphics
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, survminer
Published: 2025-09-16
Author: Zhi Zhao [aut, cre]
Maintainer: Zhi Zhao <zhi.zhao at medisin.uio.no>
BugReports: https://github.com/ocbe-uio/GPTCM/issues
License: GPL-3
Copyright: The code in src/arms.cpp is slightly modified based on the research paper implementation written by Wally Gilks.
URL: https://github.com/ocbe-uio/GPTCM
NeedsCompilation: yes
SystemRequirements: C++17
Citation: GPTCM citation info
Materials: README, NEWS
CRAN checks: GPTCM results

Documentation:

Reference manual: GPTCM.html , GPTCM.pdf
Vignettes: Introduction (source, R code)

Downloads:

Package source: GPTCM_1.1.1.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): GPTCM_1.1.1.tgz, r-oldrel (arm64): GPTCM_1.1.1.tgz, r-release (x86_64): GPTCM_1.1.1.tgz, r-oldrel (x86_64): GPTCM_1.1.1.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=GPTCM to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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