Closed MichaelClerx closed 1 month ago
@ben could you check if the bottom 6 are e.g. different names for ones above? Found them on github but not in the pyramid
Aha, here it is: https://github.com/orgs/pints-team/projects/1#card-15881685
Hi Michael,
Thanks! I've edited the comment to remove those methods I think are duplicates. Not sure what to call SIS MCMC -- it's an approach that can be applied to all samplers (and likelihood-based optimisers) essentially. Just involves heating the distribution, sampling from it, then reweighting based on importance weights. Can leave it as it stands for now though!
Thanks!
Can't find an existing ticket for this, though sure we had one at some point.
Classed as black, blue, and red in Ben's diagram
Likelihood-free
Derivative-free
DifferentialEvolutionMCMC
DreamMCMC
NestedEllipsoidSampler
EmceeHammerMCMC
PopulationMCMC
MetropolisRandomWalkMCMC
AdaptiveCovarianceMCMC
NestedRejectionSampler
SliceDoublingMCMC
SliceStepoutMCMC
1st order sensitivities
HamiltonianMCMC
MALAMCMC
MonomialGammaHamiltonianMCMC
2nd order sensitivities
Framework for all sampling (temper distribution, sample from it, reweight via importance sampling):