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. At the moment three conjugate hierarchical models are available: beta-binomial, gamma-Poisson and a 1-way analysis of variance (ANOVA).

Version: 1.0.0
Depends: R (≥ 3.3.1)
Imports: bayesplot (≥ 1.1.0), graphics, methods, rust (≥ 1.2.2), stats
Suggests: ggplot2 (≥ 2.2.1), knitr, rmarkdown, testthat
Published: 2017-11-20
Author: Paul J. Northrop [aut, cre, cph], Benjamin D. Hall [aut, cph]
Maintainer: Paul J. Northrop <p.northrop at ucl.ac.uk>
BugReports: http://github.com/paulnorthrop/bang/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: http://github.com/paulnorthrop/bang
NeedsCompilation: no
Materials: README
CRAN checks: bang results

Downloads:

Reference manual: bang.pdf
Vignettes: Hierarchical 1-way Analysis of Variance
Conjugate Hierarchical Models
Posterior Predictive Checking
Introducing bang: Bayesian Analysis, No Gibbs
Package source: bang_1.0.0.tar.gz
Windows binaries: r-devel: bang_1.0.0.zip, r-release: bang_1.0.0.zip, r-oldrel: bang_1.0.0.zip
OS X El Capitan binaries: r-release: bang_1.0.0.tgz
OS X Mavericks binaries: r-oldrel: bang_1.0.0.tgz

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