miltonian Monte Carlo can take longer per iteration (as it typically takes many “leapfrog steps” within each iteration), but the iterations typically have lower autocorrelation. So Stan might work fine with 1000 iterations in an example where BUGS would require 100,000 for good mixing. We recommend monitoring potential scale reduction statistics (<span class="math inline">\(\hat{R}\)</span>) and the effective sample size to judge when to stop (stopping when <span class="math inline">\(\hat{R}\)</span> v