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: | 1.1.3 |
| 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: | 2025-11-01 |
| DOI: | 10.32614/CRAN.package.GPTCM |
| 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 theresearch 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 |