causact: Fast, Easy, and Visual Bayesian Inference (original) (raw)
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 |
| BugReports: | https://github.com/flyaflya/causact/issues |
| License: | MIT + file |
| URL: | https://github.com/flyaflya/causact, https://www.causact.com/ |
| NeedsCompilation: | no |
| SystemRequirements: | Python and numpyro are needed for Bayesian inference computations; python (>= 3.8) with header files and shared 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 |
Documentation:
Downloads:
Linking:
Please use the canonical formhttps://CRAN.R-project.org/package=causactto link to this page.