bfw: Bayesian Framework for Computational Modeling

Derived from the work of Kruschke (2015, <ISBN:9780124058880>), the present package aims to provide a framework for conducting Bayesian analysis using Markov chain Monte Carlo (MCMC) sampling utilizing the Just Another Gibbs Sampler ('JAGS', Plummer, 2003, <http://mcmc-jags.sourceforge.net/>). The initial version includes several modules for conducting Bayesian equivalents of chi-squared tests, analysis of variance (ANOVA), multiple (hierarchical) regression, softmax regression, and for fitting data (e.g., structural equation modeling).

Version: 0.4.1
Depends: R (≥ 3.5.0)
Imports: coda (≥ 0.19-1), MASS (≥ 7.3-47), runjags (≥ 2.0.4-2)
Suggests: covr (≥ 3.1.0), circlize (≥ 0.4.4), data.table (≥ 1.12.2), dplyr (≥ 0.7.7), ggplot2 (≥ 2.2.1), knitr (≥ 1.20), lavaan (≥ 0.6-1), magrittr (≥ 1.5), officer (≥ 0.3.1), plyr (≥ 1.8.4), png (≥ 0.1-7), psych (≥ 1.7.8), rmarkdown (≥ 1.10), rvg (≥ 0.1.9), scales (≥ 0.5.0), testthat (≥ 2.0.0)
Published: 2019-11-25
Author: Øystein Olav Skaar [aut, cre]
Maintainer: Øystein Olav Skaar <bayesianfw at gmail.com>
BugReports: https://github.com/oeysan/bfw/issues/
License: MIT + file LICENSE
URL: https://github.com/oeysan/bfw/
NeedsCompilation: no
SystemRequirements: JAGS >=4.3.0 <http://mcmc-jags.sourceforge.net/>, Java JDK >=1.4 <https://www.java.com/en/download/manual.jsp>
Materials: README NEWS
CRAN checks: bfw results

Downloads:

Reference manual: bfw.pdf
Vignettes: Fit Latent Data
Fit Observed Data
Predict Metric
Plot Data
Regression
Package source: bfw_0.4.1.tar.gz
Windows binaries: r-devel: bfw_0.4.1.zip, r-release: bfw_0.4.1.zip, r-oldrel: bfw_0.4.1.zip
macOS binaries: r-release: bfw_0.4.1.tgz, r-oldrel: bfw_0.4.1.tgz
Old sources: bfw archive

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