Another benefit is reduced memory usage and increased speed: if sigmaA is close to zero/very low for d values below (say) 2 angstrom up to the high resolution limit of (say) 1 angstrom, you could shave off execution time during the starting cycles of refinement.
I guess patience is a virtue though....
Peter
Sent from my iPhone
On Nov 6, 2011, at 6:59 PM, Pavel Afonine
Hi,
Open question,
Is this 'step wise resolution increase' still necessary in the days of maximum likelihood refinement?
it not really open question. If ML target was that powerful you could do rigid body refinement using all reflections without the need of cutting off high resolution. It's not the case however, as we show in
Automatic multiple-zone rigid-body refinement with a large convergence radius. P. V. Afonine, R. W. Grosse-Kunstleve, A. Urzhumtsev and P. D. Adams J. Appl. Cryst. 42, 607-615 (2009).
STIR may be necessary for example in case of "very poor" starting model and "very high" resolution data, although the whole procedure should probably be more complex: for example, model parametrization should change as more higher resolution data is added.
Pavel
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