Accelerate Bayesian analytics workflows in 'R' through interactive modelling, visualization, and inference. Define probabilistic graphical models using directed acyclic graphs (DAGs) as a unifying language for business stakeholders, statisticians, and programmers. This package relies on interfacing with the 'numpyro' python package.
| Version: | 0.6.0 |
| Depends: | R (≥ 4.1.0) |
| Imports: | DiagrammeR (≥ 1.0.9),dplyr (≥ 1.0.8),magrittr (≥ 1.5),ggplot2 (≥ 3.4.0),rlang (≥ 1.0.2),purrr (≥ 1.0.0),tidyr (≥ 1.1.4),igraph (≥ 1.2.7),stringr (≥ 1.4.1),cowplot (≥1.1.0),forcats (≥ 0.5.0),rstudioapi (≥ 0.11),lifecycle (≥1.0.2),reticulate (≥ 1.30) |
| Suggests: | knitr,covr,testthat (≥ 3.0.0),rmarkdown,extraDistr,mvtnorm |
| Published: | 2025-09-12 |
| DOI: | 10.32614/CRAN.package.causact |
| Author: | Adam Fleischhacker [aut, cre, cph], Daniela Dapena [ctb], Rose Nguyen [ctb], Jared Sharpe [ctb] |
| Maintainer: | Adam Fleischhacker <ajf at udel.edu> |
| BugReports: | https://github.com/flyaflya/causact/issues |
| License: | MIT + fileLICENSE |
| URL: | https://github.com/flyaflya/causact,https://www.causact.com/ |
| NeedsCompilation: | no |
| SystemRequirements: | Python and numpyro are needed for Bayesianinference computations; python (>= 3.8) with header files andshared library; numpyro (= v0.12.1;https://https://num.pyro.ai/en/latest/index.html); arviz (=v0.15.1; https://https://python.arviz.org/en/stable/) |
| Citation: | causact citation info |
| Materials: | README,NEWS |
| In views: | Bayesian |
| CRAN checks: | causact results |