Package: bdribs 1.0.4.1
Saurabh Mukhopadhyay
bdribs: Bayesian Detection of Potential Risk Using Inference on Blinded Safety Data
Implements Bayesian inference to detect signal from blinded clinical trial when total number of adverse events of special concerns and total risk exposures from all patients are available in the study. For more details see the article by Mukhopadhyay et. al. (2018) titled 'Bayesian Detection of Potential Risk Using Inference on Blinded Safety Data', in Pharmaceutical Statistics (to appear).
Authors:
bdribs_1.0.4.1.tar.gz
bdribs_1.0.4.1.tar.gz(r-4.7-any)bdribs_1.0.4.1.tar.gz(r-4.6-any)
bdribs_1.0.4.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
bdribs/json (API)
| # Install 'bdribs' in R: |
| install.packages('bdribs', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- jags– Just Another Gibbs Sampler for Bayesian MCMC - binary JAGS is Just Another Gibbs Sampler. It is a program for analysis of Bayesian hierarchical models using Markov Chain Monte Carlo (MCMC) simulation not wholly unlike BUGS. JAGS was written with three aims in mind: * To have an engine for the BUGS language that runs on Unix * To be extensible, allowing users to write their own functions, distributions and samplers. * To be a plaftorm for experimentation with ideas in Bayesian modelling This package contains the 'jags' binary as well as the associated shared library modules loaded by the binary.
- c++– GNU Standard C++ Library v3
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:f811dc2268. Checks:4 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 90 | ||
| source / vignettes | OK | 139 | ||
| linux-release-x86_64 | OK | 98 | ||
| wasm-release | OK | 96 |
