BayesianTools
MCMC and SMC samplers and diagnostics for Bayesian statistics, with a focus on calibrating complex process-based models.
Downloads per year
115,264 downloads from the Posit (RStudio) CRAN mirror since 2017, through 28 October 2026
Cited 178 times on Google Scholar (as of 29 October 2026)
BayesianTools provides general-purpose samplers, plots and diagnostics for Bayesian statistics. It was written with a particular focus on calibrating complex process-based models, where every evaluation of the likelihood means running a simulation.
The model enters as an R function that returns the log-likelihood, so any simulation model that can be called from R can be calibrated, including those wrapped by rLPJGUESS and r3PG. Implemented samplers include several Metropolis variants (among them adaptive and delayed-rejection Metropolis–Hastings), the T-walk, two differential-evolution MCMCs, two DREAM samplers and a sequential Monte Carlo particle filter. Further functions cover convergence diagnostics, plotting and model comparison via the marginal likelihood and WAIC.
Authors: Florian Hartig (maintainer), Francesco Minunno, Stefan Paul. Contributors: David Cameron, Tankred Ott, Maximilian Pichler.
How to cite BayesianTools
Florian Hartig, Francesco Minunno, Stefan Paul. BayesianTools: General-Purpose MCMC and SMC Samplers and Tools for Bayesian Statistics. R package.
doi:10.32614/CRAN.package.BayesianTools.
For the citation of a specific version, run citation("BayesianTools") in R.
Citations
BayesianTools has been cited 178 times on Google Scholar as of 29 October 2026. The chart shows how they are distributed over the years, as of 20 October 2026; the 2026 figure covers the year up to that date.
Citations per year
Widely cited work citing BayesianTools
The most-cited articles that cite BayesianTools, ranked by their own citation count in OpenAlex as of 29 October 2026; the group's own papers are left out.
- Linking big models to big data: efficient ecosystem model calibration through Bayesian model emulation
- An interactive graphical interface tool for parameter calibration, sensitivity analysis, uncertainty analysis, and visualization for the Soil and Water Assessment Tool
- Beyond ecosystem modeling: A roadmap to community cyberinfrastructure for ecological data‐model integration
- Bayesian calibration of a carbon balance model PREBAS using data from permanent growth experiments and national forest inventory
- Warming may extend tree growing seasons and compensate for reduced carbon uptake during dry periods