I wonder what would be the hierarchical model given having missing in observed? I am assuming pymc3 will automatically assign a prior (not sure what it looks like) to missing values but I can not work out the full model. Would the likelihood be p(non-missing | missing, \theta)? However, in the model I am supposed to set it to be p(non-missing, missing | \theta). Please advise.