# Developing an R package using Julia for a statistical model

**URL:** <https://discourse.julialang.org/t/developing-an-r-package-using-julia-for-a-statistical-model/121320>\
**Category:** Statistics\
**Created:** [October 15, 2024, 8:56am UTC](https://discourse.julialang.org/t/developing-an-r-package-using-julia-for-a-statistical-model/121320 "2024-10-15T08:56:31Z")\
**Posts on this page:** 1\
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**Author:** ![Palli](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/palli/32/3380_2.png) [@Palli](https://discourse.julialang.org/u/Palli)\
**Post date:** [October 15, 2024, 12:42pm UTC](https://discourse.julialang.org/t/developing-an-r-package-using-julia-for-a-statistical-model/121320/11 "2024-10-15T12:42:13Z")

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It’s already possible to call Julia from R (as other have suggested for package development), and done, and note also RCall.jl for calling in other direction, with its R mode.

Note also:

> [@Julia as a universal platform for statistical software development](https://discourse.julialang.org/t/julia-as-a-universal-platform-for-statistical-software-development/113017):
>
> I just posted [a paper](https://arxiv.org/abs/2404.09309) presenting a vision of using Julia as a universal back end for statistical software development. Do things once in Julia–optimize, maintain, add features–then call from R or Python or Matlab or Stata. The motivating example is my pair of packages for Stata, which is a commercial statistics program that is popular in the social sciences and elsewhere. julia provides a C-based bridge from Stata to Julia, like JuliaCall for R. It has routines for fast data copying and provide…

And upcoming `juliac` compiler will likely make this even more compelling, but it’s strictly not needed, current tools good enough.

> I think everything is handled with this dual Julia/Python binding package

That PythonCall package is of course Python specific, but it relies on CondaPkg.jl which isn’t. I’m not sure, maybe, probably, it helps for R users installing Julia dependencies?

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