[R-sig-ME] glmmTMB: how to calculate posterior prob. of structural zero?

[Aaron Mackey]

I'm happily using glmmTMB to fit zero-inflated count models with my data,
but I'd like to also know which zeroes in my data are more likely (or not)
to be structural vs. expected from the conditional distribution. I know how
to use Bayes formula to calculate the posterior, and predict(zinb,
type="zprob") gives me the prior probabilites for each data point being
structural or not (respecting the zero inflation part of the model), and
the likelihoods for the structural components are 1 (if the data point is a
zero) or 0 (if the data point is not a zero) -- but is there a way to
extract the likelihood for each zero data point with respect to the
conditional part of the model?

thanks,
-Aaron

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