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 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 |