Yo Ari, I got a model for you to test out. Tell me what’s causing my divergences! I know how to fix it, so your challenge is to figure that out.
Link here: GitHub - bbbales2/basketball
The file is ‘westbrook.R’. The data gets loaded up and model executed in the first 16 lines. The rest is diagnostics and plots. As the model is configured, you should get 50~ divergences (4 chains, 2000 iters each).
It’s an approximate GP technique I was testing out. The story is:
I took Russell Westbrook’s made-missed shots from the 2015 season (or at least most of it – not sure if the dataset is complete). It’s an r/nba think to talk about how in 4th quarters of games Westbrook turns into Worstbrook (as opposed to Bestbrook), so the idea is maybe we could estimate Westbrook’s shooting percentage not as a single number, but as a function of the game time (and see the difference in Bestbrook and Worstbrook)
(it’s from this thread, but don’t read too far, cause this has the answer in the text: Approximate GPs with Spectral Stuff)
It took me awhile to work out where the divergences were coming from because I wasn’t sure if it was the approximation that was causing the divergences, or something weird with the data (and an exact model would have caused divergences), or something else. Anyway, seems like a good level 2 crackme. (edit: and I sure would have appreciated something more than pairplots when I was debugging this)