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: |
0.1.8 |
| Depends: |
R (≥ 3.1.2) |
| Imports: |
coda, emulator, mvtnorm, tmvtnorm, IDPmisc, Rcpp (≥ 0.12.12), ellipse, numDeriv, msm, MASS, Matrix, stats, utils, graphics, DHARMa, gap, bridgesampling |
| LinkingTo: |
Rcpp |
| Suggests: |
DEoptim, lhs, sensitivity, knitr, rmarkdown, roxygen2, testthat |
| Published: |
2023-01-30 |
| Author: |
Florian Hartig 
[aut, cre],
Francesco Minunno [aut],
Stefan Paul [aut],
David Cameron [ctb],
Tankred Ott [ctb],
Maximilian Pichler [ctb] |
| Maintainer: |
Florian Hartig <florian.hartig at biologie.uni-regensburg.de> |
| BugReports: |
https://github.com/florianhartig/BayesianTools/issues |
| License: |
GPL-3 |
| URL: |
https://github.com/florianhartig/BayesianTools |
| NeedsCompilation: |
yes |
| Materials: |
NEWS |
| In views: |
Bayesian |
| CRAN checks: |
BayesianTools results |