You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Thanks for the very clear report! The bad model isn't subsetting the TV variable inside the normal() with [i], but only in the generated quantities. If you inspect the stancode() for both models, you will see what I mean. So the estimates are the same I guess? But it's just the WAIC calc that goes wrong.
I've been thinking that what ulam() should do in these cases is make a symbol for the calculation of sigma. i.e. automatically convert the "bad" model to the "good" one. That would solve a lot of parsing issues.
If I create a model with a sigma variable all is good:
Gets me reasonable values for WAIC:
Exact same thing, but with no sigma variable is bad:
gets terrible WAIC scores:
Directory for reproduction is attached:
Bugreport.zip
The text was updated successfully, but these errors were encountered: