Data Science. Probability Distributions

> If the available data do not correspond to any known theoretical distribution (which usually happens in practice, but this does not concern anyone), then it is not recommended to use the selected template (probabilistic-statistical model).

That's where the probabilistic programming comes in.

You can write any probabilistic model you like with only some generic constraints, like differentiability etc. and use inference algorithms to compute the conditional distribution of parameters.