BayesianTools: General-Purpose MCMC and SMC Samplers and Tools for Bayesian Statistics

General-purpose MCMC and SMC samplers, as well as plot and diagnostic functions for Bayesian statistics, with a particular focus on calibrating complex system models. Implemented samplers include various Metropolis MCMC variants (including adaptive and/or delayed rejection MH), the T-walk, two differential evolution MCMCs, two DREAM MCMCs, and a sequential Monte Carlo (SMC) particle filter.

Version: 0.1.1
Depends: R (≥ 3.1.2)
Imports: coda, vioplot, emulator, mvtnorm, IDPmisc, Rcpp, ellipse, numDeriv, msm, MASS, Matrix, stats, utils, graphics
LinkingTo: Rcpp
Suggests: DEoptim, lhs, sensitivity, knitr, rmarkdown, roxygen2, testthat, gap
Published: 2017-04-05
Author: Florian Hartig [aut, cre], Francesco Minunno [aut], Stefan Paul [aut], David Cameron [ctb]
Maintainer: Florian Hartig <florian.hartig at biologie.uni-regensburg.de>
BugReports: https://github.com/florianhartig/BayesianTools/issues
License: CC BY-SA 4.0
URL: https://github.com/florianhartig/BayesianTools
NeedsCompilation: yes
Materials: NEWS
CRAN checks: BayesianTools results

Downloads:

Reference manual: BayesianTools.pdf
Vignettes: Manual for the BayesianTools R package
Package source: BayesianTools_0.1.1.tar.gz
Windows binaries: r-devel: BayesianTools_0.1.1.zip, r-release: BayesianTools_0.1.1.zip, r-oldrel: BayesianTools_0.1.1.zip
OS X El Capitan binaries: r-release: BayesianTools_0.1.1.tgz
OS X Mavericks binaries: r-oldrel: BayesianTools_0.1.1.tgz
Old sources: BayesianTools archive

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