We have many packages to fit distributions / mixture of them over `data`

with MLE or Chi2 methods. But what tools to use right now if my `data`

is already binned. I.e.

```
using Distributions, StatsBase
n = Normal()
u = Uniform(-1,1)
s() = rand() < 0.8 ? rand(n) : rand(u)
data = [s() for _=1:10^5]
binned = fit(Histogram, data)
```

Let’s say, the goal is to find `0.8`

to be the most likely weight assuming we know the center of the `normal`

and the range of the uniform.

One idea is of course using curve fitting such as `LsqFit`

and treat the PDF as a curve and bin position-bin height as x,y. Or to sample the histogram to “recover” underlying data?

What would be a ready-made way in Julia’s ecosystem?