Applying 'CUDA' 'GPUs' via 'Numba' for optimal clinical design. It allows the user to utilize a 'reticulate' 'Python' environment and run intensive Monte Carlo simulation to get the optimal cutoff for the clinical design with potential biomarker effect, which can guide the realistic clinical trials.
| Version: |
1.1.3 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
reticulate, mnormt, fields, plotly, dplyr |
| Suggests: |
knitr, rmarkdown |
| Published: |
2021-09-21 |
| Author: |
Yitao Lu  [aut,
cre],
Belaid Moa [aut],
Julie Zhou [aut],
Li Xing [aut],
Xuekui Zhang
[aut] |
| Maintainer: |
Yitao Lu <yitaolu at uvic.ca> |
| BugReports: |
https://github.com/ubcxzhang/DesignCTPB/issues |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: |
https://github.com/ubcxzhang/DesignCTPB, Y Lu (2020)
<doi:10.1002/sim.8868> |
| NeedsCompilation: |
no |
| SystemRequirements: |
OpenSSL(>= 1.0.1), NVIDIA CUDA GPU with compute
capability 3.0 or above and NVIDIA CUDA Toolkit 9.0 or above |
| Citation: |
DesignCTPB citation info |
| Materials: |
README |
| CRAN checks: |
DesignCTPB results |