Do the new deterministic variables have to be functions of parameter variables or other existing deterministic variables as in this case? In my case, I have a whole chain of derived variables and it’s only the last that I’d like the values for after sampling, akin to:
with pm.Model() as model:
# priors
...
# derived variables
...
interesting_dv = ... # interesting dv computed from earlier uninteresting vars
# likelihood
...