That’s a good point! Thanks. I modified my code to keep the original from_posterior method in place. However, I started running into some issues. With the project that I’m working on, a bunch of the variables are unobserved. Since the from_posterior function adds 3 times the width of the old posterior to the left and the right of the old posterior, the new priors of these unobserved variables become much wider than the original prior. So I’m adding some small constant instead. This prevents the blowup of the prior, while still giving the possibility of exploring values it hasn’t sampled in the past. Do you think this makes sense?
Also another question: Would the usual model comparison work? Let’s say I have two models that made use of from_posterior. Would pm.compare give sensible WAIC values (as if I ran the two models on the whole data set instead of updating my priors one by one)?