Mmmh ok, I think this NB could help you go in the right direction then. I’ve never done this personally though
Thank for the link, I think I got rough idea. Another question, if I want to design custom distribution, for instance, noncentral t like in scipy nct. What do I need in order to create a custom distribution with pymc3 and choose priors for it?
I came across new dataset and I checked which distributions fits the new dataset and it turns out to be Cauchy Distribution. I already know that there is a Cauchy function in PYMC3, but, what I am wondering is what type of priors to use where Cauchy is the likelihood distribution?
I looked into wikepedia and understood that scale parameter is greater than 0 so I am thinking halfnorm for the scale/beta parameter. but with location/alpha parameter, is it possible to assume to use norm distribution? and input the values into Cauchy likelihood distribution?