I have a question regarding the choise of the likelihood distribution. Lets assume the simple case of a normal distributed prior used in inference with some dataset evidence with an uknown distribution. If we fabricate this data using a normal distribution, choosing the right likelihood distribution is trivial, but if the datapoints are to few to be certain. what does the choise of likelihood distribution matter in pymc3?
dataset = data of length x with unknown distribution prior = pm.Normal("prior", mu=5,sd=1) likelihood = pm.Normal("likelihood", mu= prior, observed = dataset)
Here the likelihood function has a normal distribution, but what if i were to choose a beta distribution here?