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bang: Bayesian Analysis, No Gibbs

Provides functions for the Bayesian analysis of some simple commonly-used models, without using Markov Chain Monte Carlo (MCMC) methods such as Gibbs sampling. The 'rust' package <https://cran.r-project.org/package=rust> is used to simulate a random sample from the required posterior distribution, using the generalized ratio-of-uniforms method. See Wakefield, Gelfand and Smith (1991) <doi:10.1007/BF01889987> for details. At the moment three conjugate hierarchical models are available: beta-binomial, gamma-Poisson and a 1-way analysis of variance (ANOVA).

Version: 1.0.4
Depends: R (≥ 3.3.0)
Imports: bayesplot (≥ 1.1.0), graphics, rust (≥ 1.2.2), stats
Suggests: ggplot2 (≥ 2.2.1), knitr, MASS, rmarkdown, testthat
Published: 2024-07-17
DOI: 10.32614/CRAN.package.bang
Author: Paul J. Northrop [aut, cre, cph], Benjamin D. Hall [aut, cph]
Maintainer: Paul J. Northrop <p.northrop at ucl.ac.uk>
BugReports: https://github.com/paulnorthrop/bang/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://paulnorthrop.github.io/bang/, https://github.com/paulnorthrop/bang
NeedsCompilation: no
Materials: README NEWS
In views: Bayesian
CRAN checks: bang results

Documentation:

Reference manual: bang.pdf
Vignettes: Introducing bang: Bayesian Analysis, No Gibbs
Conjugate Hierarchical Models
Hierarchical 1-way Analysis of Variance
Posterior Predictive Checking

Downloads:

Package source: bang_1.0.4.tar.gz
Windows binaries: r-devel: bang_1.0.4.zip, r-release: bang_1.0.4.zip, r-oldrel: bang_1.0.4.zip
macOS binaries: r-release (arm64): bang_1.0.4.tgz, r-oldrel (arm64): bang_1.0.4.tgz, r-release (x86_64): bang_1.0.4.tgz, r-oldrel (x86_64): bang_1.0.4.tgz
Old sources: bang archive

Reverse dependencies:

Reverse suggests: rust

Linking:

Please use the canonical form https://CRAN.R-project.org/package=bang 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.
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