Thanks @paul.buerkner, much clearer now.
I am not sure I follow your point 1.
What I am saying is that anything which has a high computational cost per observation is a good candidate for efficient parallelization.
Not easy to parallelize (examples):
- normal density
- bernoulli or bernoull logit
Much better to parallelize (these require the evaluation of the log-Gamma function):
- Poisson
- Negative Binomial
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