Refactor, leaning more on PyMC and less on Bambi #64
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Closes #54
The major change in this PR is that the function we minimize is compiled directly from a PyMC model, this has several advantages. More importantly, less code to maintain and add on our side. For instance, we no longer need to define families within Kulprit, so in principle, we can use any family from Bambi. This should also simplify future extensions.
The computation of the log-likelihood group is now also PyMC's responsibility.
I did not run benchmarks in detail, as this was not the purpose of the refactoring, but it seems that we got a speed-up of ~50%.
This could also ease the direct support of PyMC models, but that's not a priority. The priority is to extend the functionality of Kulprit to support the largest possible subset of Bambi's models.