Theano shared variables with ppc seems to be the preferred way to test your model with unseen data. But there’s only very basic examples on how to use them.
For example this notebook last section shows how to make prediction by specifying a specific index for the county of a new home.
St Louis county prediction
yhat_stl = Normal(‘yhat_stl’, mu=a + b, tau=tau_y)
But this seems very inefficient to test a lot of unseen data.
Taking the example from the radon by county data, how could we fit a hierarchical model with shared variables and then sample a ppc for a dataset of unseen data? Each data point (a home) in the unseen data being associated to a particular county?