Closed HarrisonWilde closed 1 year ago
Yes, the other chains can be used to calculate Bayes factors.
This can be achieved using a state history callback, given these chains can have some utility, shall we plan to support this more directly? What do you think @torfjelde ?
IMO no because you can always access this by running step
and calling transition_for_chain
, etc.
The sample
should return just what "standard" user needs, nothing more. Then if you want to do more complex stuff, then step and callbacks should be used:)
Fair enough, I think as the package matures it may well be the case that we want to support a "friendly" way for people to diagnose potential mixing issues and so on at higher temperatures, in theory a naive way to tune a ladder would be to observe the mixing at the hottest level and if its poor then you probably havent tempered enough right? I would envision it being some boolean on the sampler that defaults to false
but returns one chain per temp when true
. Alternatively we could just export that callback you made as that might be a more Turing
approach, this can be on the backburner though. I will close this for now and if it comes up we can rethink.
IMO no because you can always access this by running
step
and callingtransition_for_chain
, etc.
You can access this by running step
, but that's a substantially lower-level interface than most users will want to deal with. I don't see what the disadvantage of including this as a named tuple in the info
field would be.
Title really, as a result of PT we end up with n chains for n inverse temperatures, one of these must be at an inverse temp of 1, i.e. the "correct" logdensity, do the other chains have any use? More a reminder to myself to read into if the others can be used for anything, but if anyone has ideas let me know here.