bridgesampling: Bridge Sampling for Marginal Likelihoods and Bayes Factors

Provides functions for estimating marginal likelihoods, Bayes factors, posterior model probabilities, and normalizing constants in general, via different versions of bridge sampling (Meng & Wong, 1996, <http://www3.stat.sinica.edu.tw/statistica/j6n4/j6n43/j6n43.htm>). Gronau, Singmann, & Wagenmakers (2020) <doi:10.18637/jss.v092.i10>.

Version: 1.0-0
Depends: R (≥ 3.0.0)
Imports: mvtnorm, Matrix, Brobdingnag, stringr, coda, parallel, scales, utils, methods
Suggests: testthat, Rcpp, RcppEigen, R2jags, rjags, runjags, knitr, rmarkdown, R.rsp, BayesFactor, rstan, rstanarm, nimble, MCMCpack
Published: 2020-02-26
Author: Quentin F. Gronau ORCID iD [aut, cre], Henrik Singmann ORCID iD [aut], Jonathan J. Forster [ctb], Eric-Jan Wagenmakers [ths], The JASP Team [ctb], Jiqiang Guo [ctb], Jonah Gabry [ctb], Ben Goodrich [ctb], Kees Mulder [ctb], Perry de Valpine [ctb]
Maintainer: Quentin F. Gronau <Quentin.F.Gronau at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/quentingronau/bridgesampling
NeedsCompilation: no
Citation: bridgesampling citation info
Materials: NEWS
In views: Bayesian
CRAN checks: bridgesampling results

Downloads:

Reference manual: bridgesampling.pdf
Vignettes: Hierarchical Normal Example JAGS
Hierarchical Normal Example Nimble
Hierarchical Normal Example Stan
Bayesian One-Sample T-Test Stan
bridgesampling: An R Package for Estimating Normalizing Constants (JSS version)
bridgesampling: An R Package for Estimating Normalizing Constants (Extended)
A Tutorial on Bridge Sampling
Package source: bridgesampling_1.0-0.tar.gz
Windows binaries: r-devel: bridgesampling_1.0-0.zip, r-release: bridgesampling_1.0-0.zip, r-oldrel: bridgesampling_1.0-0.zip
macOS binaries: r-release: bridgesampling_1.0-0.tgz, r-oldrel: bridgesampling_1.0-0.tgz
Old sources: bridgesampling archive

Reverse dependencies:

Reverse imports: BAMBI, BayesianFROC, BayesianTools, brms, metaBMA, RoBMA
Reverse suggests: bayestestR

Linking:

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