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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 |
DOI: | 10.32614/CRAN.package.DesignCTPB |
Author: | Yitao Lu |
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 |
Reference manual: | DesignCTPB.pdf |
Vignettes: |
DesignCTPB |
Package source: | DesignCTPB_1.1.3.tar.gz |
Windows binaries: | r-devel: DesignCTPB_1.1.3.zip, r-release: DesignCTPB_1.1.3.zip, r-oldrel: DesignCTPB_1.1.3.zip |
macOS binaries: | r-release (arm64): DesignCTPB_1.1.3.tgz, r-oldrel (arm64): DesignCTPB_1.1.3.tgz, r-release (x86_64): DesignCTPB_1.1.3.tgz, r-oldrel (x86_64): DesignCTPB_1.1.3.tgz |
Old sources: | DesignCTPB archive |
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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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