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

General-purpose MCMC and SMC samplers, as well as plots 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.


Reference manual

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install.packages("BayesianTools")

0.1.9 by Florian Hartig, 7 months ago


https://github.com/florianhartig/BayesianTools, https://florianhartig.github.io/BayesianTools/


Report a bug at https://github.com/florianhartig/BayesianTools/issues


Browse source code at https://github.com/cran/BayesianTools


Authors: Florian Hartig [aut, cre] (ORCID: , Francesco Minunno [aut] , Stefan Paul [aut] , David Cameron [ctb] , Tankred Ott [ctb] , Maximilian Pichler [ctb]


Documentation:   PDF Manual  


GPL-3 license


Imports coda, emulator, mvtnorm, tmvtnorm, IDPmisc, Rcpp, ellipse, numDeriv, msm, MASS, Matrix, stats, utils, graphics, DHARMa, gap, bridgesampling

Suggests DEoptim, sensitivity, knitr, rmarkdown, roxygen2, testthat

Linking to Rcpp


Imported by DPTM, eDITH, rsofun, skytrackr.

Suggested by NRMstatsML, apsimx, pttstability, r3PG.

Enhanced by DHARMa.


See at CRAN