Here’s code to simulate and fit hierarchical data. It uses my reduced-redundant-computation trick, but there’s still a final call to normal() at the end that has lots of input if you choose large values for any of the data-simulation parameters at the top of the R script. Increasing num_trials should have the most targeted impact on that final likelihood call; increasing the others will increase the input to the likelihood but will also increase the amount of computation that has to happen before the likelihood.
hwg_fast.r (8.5 KB) hwg_fast.stan (3.4 KB) helper_functions.r (5.0 KB)