Package: mcmcderive 0.1.2

Joe Thorley

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:Joe Thorley [aut, cre], Poisson Consulting [cph, fnd]

mcmcderive_0.1.2.tar.gz
mcmcderive_0.1.2.zip(r-4.7-any)mcmcderive_0.1.2.zip(r-4.6-any)mcmcderive_0.1.2.zip(r-4.5-any)
mcmcderive_0.1.2.tgz(r-4.6-any)mcmcderive_0.1.2.tgz(r-4.5-any)
mcmcderive_0.1.2.tar.gz(r-4.7-any)mcmcderive_0.1.2.tar.gz(r-4.6-any)
mcmcderive_0.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
mcmcderive/json (API)

# Install 'mcmcderive' in R:
install.packages('mcmcderive', repos = c('https://cranhaven.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/poissonconsulting/mcmcderive/issues

On CRAN:

Conda:

archivedpackagesr-universe

3.83 score 5 stars 9 packages 7 scripts 353 downloads 1 exports 21 dependencies

Last updated from:b25f8a3d0b (on package/mcmcderive). Checks:2 NOTE, 7 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develNOTE111
source / vignettesOK213
linux-releaseOK155
macos-releaseOK97
macos-oldrelOK103
windows-develNOTE78
windows-releaseOK84
windows-oldrelOK87
wasm-releaseOK89

Exports:mcmc_derive

Dependencies:abindchkclicodaextrasgenericsgluelatticelifecyclemagrittrmcmcrnlistpillarpkgconfigpurrrrlangtermtibbleuniversalsutf8vctrs

Readme and manuals

Help Manual

Help pageTopics
MCMC Derivemcmc_derive mcmc_derive.mcmc mcmc_derive.mcmc.list mcmc_derive.mcmcr mcmc_derive.mcmcrs mcmc_derive.nlist mcmc_derive.nlists