Package: mcmcderive 0.1.2.9007

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], Ayla Pearson [aut], Kirill Müller [aut], Nadine Hussein [ctb], Poisson Consulting [cph, fnd]

mcmcderive_0.1.2.9007.tar.gz
mcmcderive_0.1.2.9007.zip(r-4.7)mcmcderive_0.1.2.9007.zip(r-4.6)mcmcderive_0.1.2.9007.zip(r-4.5)
mcmcderive_0.1.2.9007.tgz(r-4.6-any)mcmcderive_0.1.2.9007.tgz(r-4.5-any)
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mcmcderive_0.1.2.9007.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://poissonconsulting.r-universe.dev', 'https://cloud.r-project.org'))

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

Pkgdown/docs site:https://poissonconsulting.github.io

On CRAN:

Conda:

derived-parametersmcmcmcmcr

5.31 score 9 packages 6 scripts 280 downloads 2 exports 21 dependencies

Last updated from:5cf5493a20. Checks:2 NOTE, 7 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64NOTE138
source / vignettesOK176
linux-release-x86_64OK130
macos-release-arm64OK108
macos-oldrel-arm64OK73
windows-develNOTE69
windows-releaseOK79
windows-oldrelOK87
wasm-releaseOK117

Exports:expression_vectorizemcmc_derive

Dependencies:abindchkclicodaextrasgenericsgluelatticelifecyclemagrittrmcmcrnlistpillarpkgconfigpurrrrlangtermtibbleuniversalsutf8vctrs

Readme and manuals

Help Manual

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