Hi Ben,
Thanks for the quick answer.
A bit of background, I have some CMR data of smolts migrating out of the freshwater system but the CMR experiments sometime start when smolts have started migrating.
this means that some years there is a fraction of the run that we don't sample, so I am also trying to model this process too based on years when we have confidence that we capture the whole run (i.e.
I have a model that runs in jags but its very slow to converge and that's why I'm trying to switch to Nimble.
I tried just copy-pasting the jags code but I have already picked up on some things I will have to change in terms of data.frame formatting so that's why Im just slowly building the model in Nimble and the version I'm sharing here just has the daily abundances:
pNm[1:I_nDays]
and the fisrt captures:
data_RT[i] ~ dbin(q[i] , Nm[I_RT_y[i]])
I am not expecting anything from the inference process at this point, just trying to understand how to adjust my coding