Hi Douglas,
Am I correct in thinking that in phenix you are basically maximizing eqn 4 (a type of Rice distribution)?
yes, correct: formula (4) is what's called ML target in phenix.refine.
I had always assumed that experimental sigmas were somehow lumped into the alpha and beta parameters (esp. given your discussion in section 2.3). In principle they could be, right?
Yes, they could be.
In any case, I wonder if your example of rigid-body refinement actually argues for incorporating experimental sigmas --- since high-res data is on average the most uncertain, incorporating sigmas would downweight high-res data most, and cutting high res data is really just a crude way of downweighting it.
Right, making use of experimental sigmas, one way or another, is in todo list. All the best, Pavel