Open kaitejohnson opened 1 month ago
I don't know the extent to which this would improve forecast accuracy. It should make NUTS slightly easier to run. Aside from those, if you'd like to make statements about the relative sizes of the different trends/components in the model then I think it's useful to have the sum-to-zeros.
This would also have the (imo) salutary effect of making the n=1 site model reduce to a non-hierarchical model, which is not currently the case. CC @damonbayer @sbidari
Goal
Explore how this might work for the aspatial model, might improve identifiability
Context
Suggestion from @athowes to improve identifiability, in particular might be helpful when there are deviations that could be due to site/subpopulation level changes and also could be due to deviation in "central/global" $R(t)$ Suggests something like:
sum(subpop_level_errors[t]) ~ normal(0, <small_number> *<n_subpops>)
Requirements
Out of scope for this PR