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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, <https://mcmc-jags.sourceforge.io>). 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: | 0.4.2 |
Depends: | R (≥ 3.5.0) |
Imports: | circlize (≥ 0.4.4), coda (≥ 0.19-1), data.table (≥ 1.12.2), dplyr (≥ 0.7.7), ggplot2 (≥ 2.2.1), graphics, grDevices, grid, magrittr (≥ 1.5), MASS (≥ 7.3-47), officer (≥ 0.3.1), parallel, plyr (≥ 1.8.4), png (≥ 0.1-7), runjags (≥ 2.0.4-2), rvg (≥ 0.1.9), scales (≥ 0.5.0), stats, utils |
Suggests: | testthat (≥ 3.0.0), knitr (≥ 1.20), lavaan (≥ 0.6-1), psych (≥ 1.7.8), rmarkdown (≥ 1.10) |
Published: | 2022-02-22 |
DOI: | 10.32614/CRAN.package.bfw |
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 <https://mcmc-jags.sourceforge.io>, Java JDK >=1.4 <https://www.java.com/en/download/manual.jsp> |
Materials: | README NEWS |
CRAN checks: | bfw results |
Reference manual: | bfw.pdf |
Vignettes: |
Fit Latent Data Fit Observed Data Predict Metric Plot Data Regression |
Package source: | bfw_0.4.2.tar.gz |
Windows binaries: | r-devel: bfw_0.4.2.zip, r-release: bfw_0.4.2.zip, r-oldrel: bfw_0.4.2.zip |
macOS binaries: | r-release (arm64): bfw_0.4.2.tgz, r-oldrel (arm64): bfw_0.4.2.tgz, r-release (x86_64): bfw_0.4.2.tgz, r-oldrel (x86_64): bfw_0.4.2.tgz |
Old sources: | bfw archive |
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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.