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DesignCTPB: Design Clinical Trials with Potential Biomarker Effect
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 |
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=DesignCTPB
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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