Package: mcmcderive 0.1.2.9003
mcmcderive: Derive MCMC Parameters
Generates derived parameter(s) from Monte Carlo Markov Chain (MCMC) samples using R code. This allows Bayesian models to be fitted without the inclusion of derived parameters which add unnecessary clutter and slow model fitting. For more information on MCMC samples see Brooks et al. (2011) <isbn:978-1-4200-7941-8>.
Authors:
mcmcderive_0.1.2.9003.tar.gz
mcmcderive_0.1.2.9003.zip(r-4.5)mcmcderive_0.1.2.9003.zip(r-4.4)mcmcderive_0.1.2.9003.zip(r-4.3)
mcmcderive_0.1.2.9003.tgz(r-4.4-any)mcmcderive_0.1.2.9003.tgz(r-4.3-any)
mcmcderive_0.1.2.9003.tar.gz(r-4.5-noble)mcmcderive_0.1.2.9003.tar.gz(r-4.4-noble)
mcmcderive_0.1.2.9003.tgz(r-4.4-emscripten)mcmcderive_0.1.2.9003.tgz(r-4.3-emscripten)
mcmcderive.pdf |mcmcderive.html✨
mcmcderive/json (API)
NEWS
# Install 'mcmcderive' in R: |
install.packages('mcmcderive', repos = c('https://poissonconsulting.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/poissonconsulting/mcmcderive/issues
Last updated 21 days agofrom:d5e2aebdcb. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 18 2024 |
R-4.5-win | OK | Nov 18 2024 |
R-4.5-linux | OK | Nov 18 2024 |
R-4.4-win | OK | Nov 18 2024 |
R-4.4-mac | OK | Nov 18 2024 |
R-4.3-win | OK | Nov 18 2024 |
R-4.3-mac | OK | Nov 18 2024 |
Exports:expression_vectorizemcmc_derive
Dependencies:abindchkclicodaextrasfansigenericsgluelatticelifecyclemagrittrmcmcrnlistpillarpkgconfigpurrrrlangtermtibbleuniversalsutf8vctrs
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Convert New Expression | expression_vectorize |
MCMC Derive | mcmc_derive mcmc_derive.mcmc mcmc_derive.mcmc.list mcmc_derive.mcmcr mcmc_derive.mcmcrs mcmc_derive.nlist mcmc_derive.nlists |