Package: bang 1.0.4.9000

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).

Authors:Paul J. Northrop [aut, cre, cph], Benjamin D. Hall [aut, cph]

bang_1.0.4.9000.tar.gz
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manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
bang/json (API)

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

Bug tracker:https://github.com/paulnorthrop/bang/issues

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

Datasets:
  • coagulation - Coagulation time data
  • pump - Pump-failure data
  • rat - Rat tumor data
  • temp1 - Mid 21st Century Global Temperature Projection Data
  • temp2 - Late 21st Century Global Temperature Projection Data
  • weight_gain - Weight Gained by Rats

On CRAN:

Conda:

anovabayesianbetabinomialgammagibbshierarchicalpoisson

6.46 score 4 stars 41 scripts 4.4k downloads 7 exports 44 dependencies

Last updated from:3ce8d72b60. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK221
source / vignettesOK242
linux-release-x86_64OK168
macos-release-arm64OK110
macos-oldrel-arm64OK91
windows-develOK116
windows-releaseOK118
windows-oldrelOK103
wasm-releaseOK225

Exports:hanova1hefpp_checkset_user_priorsim_pred_beta_binomsim_pred_gamma_poissim_pred_hanova1

Dependencies:abindbackportsbayesplotcheckmateclicpp11distributionaldplyrfarvergenericsggplot2ggridgesgluegtableisobandlabelinglifecyclemagrittrmatrixStatsnumDerivpillarpkgconfigplyrposteriorpurrrR6RColorBrewerRcppRcppArmadilloreshape2rlangrustS7scalesstringistringrtensorAtibbletidyrtidyselectutf8vctrsviridisLitewithr

Conjugate Hierarchical Models
Beta-binomial model | Gamma-Poisson Model | References
Rendered frombang-b-hef-vignette.Rmdusingknitr::rmarkdown

Last update: 2025-11-18
Started: 2020-02-21

Hierarchical 1-way Analysis of Variance
Late 21st Century Global Temperature Projection Data | Coagulation time data | Appendix | Marginal posterior density of $\boldsymbol{\mathbf{\phi}}$ | A special case | The conditional posterior density of $\boldsymbol{\mathbf{\theta}}$ given $\boldsymbol{\mathbf{\phi}}$ | Factorisations for simulation | References
Rendered frombang-c-anova-vignette.Rmdusingknitr::rmarkdown

Last update: 2025-11-18
Started: 2020-02-21

Introducing bang: Bayesian Analysis, No Gibbs
The generalized ratio-of-uniforms method as an alternative to MCMC | An example: hierarchical beta-binomial model | References
Rendered frombang-a-vignette.Rmdusingknitr::rmarkdown

Last update: 2020-02-24
Started: 2020-02-21

Posterior Predictive Checking
Beta-binomial model | Gamma-Poisson model | One-way Hierarchical ANOVA | References
Rendered frombang-d-ppc-vignette.Rmdusingknitr::rmarkdown

Last update: 2020-02-24
Started: 2020-02-21