# Designated Target Audience of Julia 1.0?

**URL:** https://discourse.julialang.org/t/designated-target-audience-of-julia-1-0/11804
**Category:** Community
**Created:** [June 20, 2018, 1:55am UTC](https://discourse.julialang.org/t/designated-target-audience-of-julia-1-0/11804 "2018-06-20T01:55:31Z")
**Posts on this page:** 1
**Showing post:** 21

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### Author: ![jonathanBieler](https://avatars.discourse-cdn.com/v4/letter/j/82dd89/32.png) [@jonathanBieler](https://discourse.julialang.org/u/jonathanBieler)
#### Post date: [June 20, 2018, 11:49am UTC](https://discourse.julialang.org/t/designated-target-audience-of-julia-1-0/11804/21 "2018-06-20T11:49:35Z")

</div>

I’m not very well-versed in R but I find it quite horrible for statistics, for example in Julia if you want to compute the pdf of a Normal distribution with parameters (μ,σ) at value x you do :

```
pdf(Normal(μ,σ),x)

```

In R you do:

```
dnorm(x,μ,σ)

```

If you want to truncated Normal between zero and one you do:

```
pdf(Truncated(Normal(μ,σ),0,1),x)

```

In R you do:

```
google for a package
...
dtrunc(x, spec="norm", a=0, b=1, mean=μ, sd=σ)

```

If you want a mixture of two Gaussians:

```
MixtureModel([Normal(μ1,σ1), Normal(μ2,σ2)],[1/2,1/2])

```

In R you do:

```
google for a package
...

```

If you want a BetaBinomial:

```
pdf(BetaBinomial(n,α,β),x)

```

In R you do:

```
google for a package
...

```

In Julia you have nice atomic concepts that are composable, while in R you just have a bunch of functions with unreadable names and packages with no common semantics.

I would be curious to see how this translates in R:

```julia
[f(D) for f in [mean,std,entropy], D in [Normal(0,1), BetaBinomial(10,0.1,0.1), Truncated(Normal(0,1),0,1)]]

```

Ironically the biggest issue with Distributions.jl is that it uses Rmath, but hopefully that will get fixed in time.

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