RHMC... is it self-adapting like NUTS?



I have a very simple model in mind to try out RHMC… but before diving into this I was wondering if the RHMC implementation in Stan includes the NUTS trick?

So is the RHMC implementation as user-friendly as NUTS or more like plain vanilla HMC?

I found that even with experience with NUTS it is hard to figure out stable sampling parameters for vanilla HMC (at least for me).



Yes. See Michael’s paper on GeoNUTS (generalizes no-U-turn to Riemannian):

Also see the one on SoftAbs (stable metric that can be computed):

The ODE integrators haven’t been generalized for higher-order derivatives. And I think there’s still a tuning parameter in there somewhere—I don’t know how well adaptation has been tuned.