How can i sample posteriors from training-data, run posterior predictive on testing data (with complex factor graph)

[jessegrabowski]

I didn’t use arviz. It’s the same as the code i posted here:

Is this half cauchy model correct?

The best practice for out of sample prediction is to: Use pm.MutableData objects to hold your data Include size=X.shape[0] in the likelihood term Use pm.set_data together with pm.sample_posterior_predictive to get out-of-sample predictions. Here is how it looks with your model: with pm.Model() as model: # Here's the mutable data X_pt = pm.MutableData('X', X_train) y_pt = pm.MutableData('y', y_train) α = pm.Normal("α", mu=0, sigma=1) β = pm.Normal("β", mu=0, sigma=1) …