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
If predictions are 0 (therefore on the linear predictor scale log(0)=-Inf), then getting derivatives for use in variance estimation is tricky. Numerically (grad()), it falls over.
This seems like it would be relatively rare (predictions of exact zeros seem unlikely due to the smooth nature of the model).
The text was updated successfully, but these errors were encountered:
This is a somewhat unlikely bug. It relies on a case where we have (numerically) zero predictions, which barely ever happens. It's actually pretty hard to reproduce.
If predictions are 0 (therefore on the linear predictor scale
log(0)=-Inf
), then getting derivatives for use in variance estimation is tricky. Numerically (grad()
), it falls over.This seems like it would be relatively rare (predictions of exact zeros seem unlikely due to the smooth nature of the model).
The text was updated successfully, but these errors were encountered: