# Random variables in Julia (working list)

**URL:** https://discourse.julialang.org/t/random-variables-in-julia-working-list/48762
**Category:** Statistics
**Tags:** distributions
**Created:** [October 21, 2020, 5:18pm UTC](https://discourse.julialang.org/t/random-variables-in-julia-working-list/48762 "2020-10-21T17:18:20Z")
**Posts on this page:** 1
**Showing post:** 12

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### Author: ![johnczito](https://avatars.discourse-cdn.com/v4/letter/j/53a042/32.png) [@johnczito](https://discourse.julialang.org/u/johnczito)
#### Post date: [October 22, 2020, 10:07am UTC](https://discourse.julialang.org/t/random-variables-in-julia-working-list/48762/12 "2020-10-22T10:07:06Z")

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I always liked these remarks:

> [@Reworking Distributions.jl](https://discourse.julialang.org/t/reworking-distributions-jl/32339/33):
>
> All I was suggesting is that I prefer Distributions.jl to be an implementation of the distributions which have some sort of a closed-form characterization (this is obviously subjective, but let’s say you need at least a pdf and IID sampling; CDF/quantiles are optional, having at least a mean is nice when known in closed form, other moments as available). So, to me, the ideal Distributions.jl is just code implementing formulas and tables usually found in the appendix of some classical stats text…

It’s useful to have a package with the modest ambition of providing `Julia`’s answer to the `p-`, `q-`, `r-` functions for the standard distributions, which `Distributions.jl` currently does more or less well.

When it comes to all the fancy probabilistic programming stuff, is the overarching vision that `Julia`’s implementation of “the gamma distribution” is ultimately a special case of the same framework that addresses posterior sampling over tree spaces and things like that?

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