The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.

bayesMeanScale: Bayesian Post-Estimation on the Mean Scale

Computes Bayesian posterior distributions of predictions, marginal effects, and differences of marginal effects for various generalized linear models. Importantly, the posteriors are on the mean (response) scale, allowing for more natural interpretation than summaries on the link scale. Also, predictions and marginal effects of the count probabilities for Poisson and negative binomial models can be computed.

Version: 0.1.4
Depends: R (≥ 3.5.0)
Imports: bayestestR (≥ 0.13.2), data.table (≥ 1.15.2), magrittr (≥ 2.0.3), posterior (≥ 1.5.0)
Suggests: flextable (≥ 0.9.5), knitr (≥ 1.45), rmarkdown (≥ 2.26), rstanarm (≥ 2.32.1), testthat (≥ 3.0.0)
Published: 2024-05-30
DOI: 10.32614/CRAN.package.bayesMeanScale
Author: David M. Dalenberg [aut, cre]
Maintainer: David M. Dalenberg <dalenbe2 at gmail.com>
BugReports: https://github.com/dalenbe2/bayesMeanScale/issues
License: GPL (≥ 3)
URL: https://github.com/dalenbe2/bayesMeanScale
NeedsCompilation: no
Materials: README NEWS
CRAN checks: bayesMeanScale results

Documentation:

Reference manual: bayesMeanScale.pdf
Vignettes: Introduction to 'bayesMeanScale'

Downloads:

Package source: bayesMeanScale_0.1.4.tar.gz
Windows binaries: r-devel: bayesMeanScale_0.1.4.zip, r-release: bayesMeanScale_0.1.4.zip, r-oldrel: bayesMeanScale_0.1.4.zip
macOS binaries: r-release (arm64): bayesMeanScale_0.1.4.tgz, r-oldrel (arm64): bayesMeanScale_0.1.4.tgz, r-release (x86_64): bayesMeanScale_0.1.4.tgz, r-oldrel (x86_64): bayesMeanScale_0.1.4.tgz
Old sources: bayesMeanScale archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=bayesMeanScale to link to this page.

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.