When running a model with different seeds, I’ve observed that often, more divergences mean lower rhat score. I would have expected the opposite to be the case, but I’m not an expert with Hamiltonian Monte Carlo, so maybe someone can answer whether (a) this is because of some counterintuitive fact about Hamiltonian Monte Carlo (I’m using NUTS by the way), or (b) because divergences are discarded and don’t count for the rhat score.

Thanks!