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, <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
Published:
2022年02月22日
Author:
Øystein Olav Skaar [aut, cre]
Maintainer:
Øystein Olav Skaar <bayesianfw at gmail.com>
NeedsCompilation:
no
SystemRequirements:
JAGS >=4.3.0 <https://mcmc-jags.sourceforge.io>,
Java JDK >=1.4 <https://www.java.com/en/download/manual.jsp>
Documentation:
Downloads:
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