nested sampling

Today in our weekly meeting, Hou gave Goodman, Foreman-Mackey, and I a tutorial on nested sampling, explaining how his extension of diffusive nested sapling—using the affine-invariant MCMC sampler—can sample the posterior PDF and compute the marginalized likelihood (the Bayes factor or evidence). I still don't completely understand; the method is certainly not trivial. We are hoping the affine-invariant sampler will create performance advantages over other implementations, and we have lots of evidence (generated by and with Brewer) that diffusive nested sampling is awesome for multi-modal posterior PDFs.


  1. I apologise for sending you down this path! Although hopefully it will lead to awesomeness.

    It certainly is a non-trivial method: https://twitter.com/brendonbrewer/status/3391462450

  2. A bit late, but... do you have any updates on this method? I am currently playing with diffusive NS, and I would definitely be interested in any tweaks you guys have thought up!