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?