Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
1 participant
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
Hi Darren:
If you like, something not so standard: sampling the posterior in the logistic regression with a bouncy particle sampler using our package ZigZagBoomerang.jl (please excuse I am using that programming language...). This is a nonreversible sampler with a continuous (piecewise linear) trajectory, so the trace is really a line and not a sequence of points. This is maybe most interesting because from here it is only one step to the case of a sparse problem (using a spike and slab prior as in https://arxiv.org/abs/2103.08478).
Here I am just using the package, but perhaps also a more elementary version which illustrates how the algorithm can be implemented would be worthwhile, which then also can be ported.
The figure shows the beginning of the continuous sampler trace in β₁-β₂-plane.