This package is considered a duplicate. The official version of this package is found at:https://mirkoth.r-universe.dev/BayesRS

Package: BayesRS 0.1.3

Mirko Thalmann

BayesRS: Bayes Factors for Hierarchical Linear Models with Continuous Predictors

Runs hierarchical linear Bayesian models. Samples from the posterior distributions of model parameters in JAGS (Just Another Gibbs Sampler; Plummer, 2017, <http://mcmc-jags.sourceforge.net>). Computes Bayes factors for group parameters of interest with the Savage-Dickey density ratio (Wetzels, Raaijmakers, Jakab, Wagenmakers, 2009, <doi:10.3758/PBR.16.4.752>).

Authors:Mirko Thalmann [aut, cre], Marcel Niklaus [aut], Klaus Oberauer [ths], John Kruschke [ctb]

BayesRS_0.1.3.tar.gz
BayesRS_0.1.3.tar.gz(r-4.7-any)BayesRS_0.1.3.tar.gz(r-4.6-any)
BayesRS_0.1.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
BayesRS/json (API)

# Install 'BayesRS' in R:

install.packages('BayesRS', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Uses libs:

jags– Just Another Gibbs Sampler for Bayesian MCMC - binary JAGS is Just Another Gibbs Sampler. It is a program for analysis of Bayesian hierarchical models using Markov Chain Monte Carlo (MCMC) simulation not wholly unlike BUGS. JAGS was written with three aims in mind: * To have an engine for the BUGS language that runs on Unix * To be extensible, allowing users to write their own functions, distributions and samplers. * To be a plaftorm for experimentation with ideas in Bayesian modelling This package contains the 'jags' binary as well as the associated shared library modules loaded by the binary.
c++– GNU Standard C++ Library v3

Datasets: