Plotting univariate distributions is really simple:

```
using Distributions
using StatsPlots
norm = fit(Normal, rand(100))
plot(norm)
```

However, how would I plot a multivariate distribution? The above code doesn’t work for the multivariate case:

```
mvnorm = fit(MvNormal, [rand(0.0:100.0, 100) rand(0.0:100.0, 100)]')
julia> plot(mvnorm)
ERROR: MethodError: no method matching iterate(::MvNormal{Float64,PDMats.PDMat{Float64,Array{Float64,2}},Array{Float64,1}})
Closest candidates are:
iterate(::Core.SimpleVector) at essentials.jl:600
iterate(::Core.SimpleVector, ::Any) at essentials.jl:600
iterate(::ExponentialBackOff) at error.jl:218
...
```

Here’s an example from Wikipedia of what an ideal output would look like: