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On the recordRead 4 Oct 202610 facts
jagstargets
On the record
- Analysis outputs
- The workflow can create posterior draws, summary statistics and convergence diagnostics, and deviance information criterion results.docs.ropensci.org · read 4 Oct 2026
- Distribution and license
- The documentation offers installation from CRAN or the GitHub development version, and identifies the license as MIT.docs.ropensci.org · read 4 Oct 2026
- Efficiency
- Pipelines can skip expensive steps when their results are already up to date and automatically parallelize computation.docs.ropensci.org · read 4 Oct 2026
- Integrations
- jagstargets works with JAGS, R2jags, targets, and posterior.docs.ropensci.org · read 4 Oct 2026
- Intended users
- The documentation says users should be familiar with targets, Bayesian statistics, and JAGS; prior experience with rjags or R2jags helps.docs.ropensci.org · read 4 Oct 2026
- Multiple models
- You can supply multiple JAGS model files, which run on the same dataset.docs.ropensci.org · read 4 Oct 2026
- Purpose
- jagstargets creates reproducible pipelines for Bayesian data analysis with JAGS, designed for Bayesian statisticians.docs.ropensci.org · read 4 Oct 2026
- Requirements
- Users must install JAGS, rjags, and R2jags before installing jagstargets.docs.ropensci.org · read 4 Oct 2026
- Support
- Users having trouble can ask for help in the project's GitHub discussions forum.docs.ropensci.org · read 4 Oct 2026
- Workflow
- Its tar_jags() function declares targets for fitting JAGS models and managing their workflow through targets.docs.ropensci.org · read 4 Oct 2026
