R interface for JuliaBUGS.jl from the rjuliabugs package (#389)

# Final Report: GSoC '25  
**Contributor Name**: Mateus Maia  
**Organization**: Turing.jl  
**Mentors**: Xianda Sun, Robert Goudie  
**Project**: `rjuliabugs` – R Interface for JuliaBUGS.jl  

## Projects  
This PR has been created as part of the Google Summer of Code in the
"rjuliabugs – R Interface for JuliaBUGS.jl" project.
I have developed the `rjuliabugs` R package, which provides a bridge
between R and JuliaBUGS, the BUGS-style Bayesian modeling interface
developed in Julia. With this package, R users can run BUGS models
through JuliaBUGS, leveraging advanced inference engines such as
Hamiltonian Monte Carlo (HMC) while staying within the R environment.

The package integrates seamlessly with R’s post-processing ecosystem,
including tools like `bayesplot`, `posterior`, and `coda`, allowing for
diagnostics and visualization of Bayesian models directly from R.

The final result can be find in this repository:

https://github.com/MateusMaiaDS/rjuliabugs

and with a clear documentation through:

https://mateusmaiads.github.io/rjuliabugs/

## Features  
Able to perform the following:  
- Run BUGS models using JuliaBUGS from R  
- Interface with R visualization and post-processing tools (`bayesplot`,
`posterior`, `coda`)
- Seamless translation of BUGS code into Julia for efficient execution  

## Constraints and Future Improvement  
Currently, `rjuliabugs` requires an initial setup (`setup_juliaBUGS()`)
for Julia dependencies and is optimized for running one model at a time.
Future improvements could include:
- Improved progress bars for the sampler for running `rjuliabugs` inside
the R console inside the R studio.
- Keep adding more examples of models that can be used using JuliaBUGS
within the R library.
- Although `JuliaCall` can be efficient, a better integration between
and Julia may upcome in the future which may speed-up the initialization
when doing (`setup_juliaBUGS()`).

## Acknowledgements
Thank you Turing.jl and Google Summer of Code for this amazing
opportunity. I learned and applied my coding skills during this event.
Special thanks to my mentors Xianda Sun and Robert Goudie for their
guidance and support throughout the project.

---------

Co-authored-by: Xianda Sun <[email protected]>
Co-authored-by: Xianda Sun <[email protected]>

Author: MateusMaiaDS

JuliaBUGS/docs/src/R_interface.md

@@ -1,11 +1,25 @@
 # R Interface
 
-Interoperation between Julia and R is very solid and simple to use.
+[**RJuliaBUGS**](https://mateusmaiads.github.io/rjuliabugs/) lets you run BUGS models from R using Julia's fast sampling algorithms.
 
-Here are some very useful packages:
+Created by [Mateus Maia](https://github.com/MateusMaiaDS) as part of Google Summer of Code 2025.
 
-- [`RCall.jl`](https://github.com/JuliaInterop/RCall.jl): interaction with R runtime.
-- [`RData.jl`](https://github.com/JuliaData/RData.jl): reading and writing R data files.
-- [`DataFrames.jl`](https://github.com/JuliaData/DataFrames.jl): `pandas` and `dplyr` for Julia.
-- [`CSV.jl`](https://github.com/JuliaData/CSV.jl): CSV file reading and writing.
-- [`JSON.jl`](https://github.com/JuliaIO/JSON.jl), [`JSON3.jl`](https://github.com/quinnj/JSON3.jl), [`Serde.jl`](https://github.com/bhftbootcamp/Serde.jl): JSON file reading and writing.
+## What is RJuliaBUGS?
+
+RJuliaBUGS connects R to JuliaBUGS. You write models in BUGS syntax and run them from R, but they execute using Julia's modern samplers like Hamiltonian Monte Carlo (HMC).
+
+**Key benefits:**
+- Keep your existing BUGS models
+- Run models faster with Julia's algorithms
+- Stay in R for all analysis
+- Works with `bayesplot`, `posterior`, `coda`, and other R packages
+
+## Related Julia Packages
+
+For R users working with Julia:
+
+- [`RCall.jl`](https://github.com/JuliaInterop/RCall.jl) - Run R from Julia
+- [`RData.jl`](https://github.com/JuliaData/RData.jl) - Read/write R data files
+- [`DataFrames.jl`](https://github.com/JuliaData/DataFrames.jl) - Data manipulation (like `dplyr`)
+- [`CSV.jl`](https://github.com/JuliaData/CSV.jl) - Work with CSV files
+- [`JSON.jl`](https://github.com/JuliaIO/JSON.jl), [`JSON3.jl`](https://github.com/quinnj/JSON3.jl) - Work with JSON data