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.

Maintainer: Florian Hartig <florian.hartig at biologie.uni-regensburg.de>

Author(s): Florian Hartig*, Francesco Minunno*, Stefan Paul*, David Cameron*

Install package and any missing dependencies by running this line in your R console:

install.packages("BayesianTools")

Depends R (>= 3.1.2)
Imports coda, vioplot, emulator, mvtnorm, IDPmisc, Rcpp, ellipse, numDeriv, msm, MASS, Matrix, stats, utils, graphics
Suggests DEoptim, lhs, sensitivity, knitr, rmarkdown, roxygen2, testthat, gap
Enhances
Linking to Rcpp
Reverse
depends
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imports
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suggests
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enhances
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linking to

Package BayesianTools
Materials
URL https://github.com/florianhartig/BayesianTools
Task Views
Version 0.1.0
Published 2017-02-06
License CC BY-SA 4.0
BugReports https://github.com/florianhartig/BayesianTools/issues
SystemRequirements
NeedsCompilation yes
Citation
CRAN checks BayesianTools check results
Package source BayesianTools_0.1.0.tar.gz