UCL/rmcmc

Robust Markov chain Monte Carlo methods in R

Stars: 8
Forks: 8
Open beginner issues: 0
Indexed issues: 8

Dominant language: R
License: No license data
Last GitHub push: Sep 7, 2026
Latest indexed: Sep 20, 2026
Contributing guide: Contributing guide
Code of conduct: Code of conduct
Beginner labels: No beginner labels indexed
PR merge metrics: No merged PRs in 30d

Beginner friendly Everything

Open All

Allow easy comparison of samplers with single function Open

enhancement

Difficulty 5/5 Over a week Newbie friendliness 35/100

UCL/rmcmc#141 · Opened Aug 3, 2026
Warm-up cannot be traced when using heterogeneous adapter stages Open

bug

Difficulty 4/5 3-5 days Newbie friendliness 35/100

UCL/rmcmc#138 · Opened Jul 22, 2026
Allow specifying initial state as a dimension-dependent function Open

enhancement

Difficulty 4/5 3-5 days Newbie friendliness 25/100

UCL/rmcmc#135 · Opened Jul 16, 2026
Allow easily sampling from `posteriordb` models Open

enhancement

Difficulty 4/5 3-5 days Newbie friendliness 45/100

UCL/rmcmc#129 · 1 comment · Opened Jul 9, 2026
Add Adam-based shape adapter(s) as alternative to variance/covariance shape adapters Open

enhancement

Difficulty 5/5 Over a week Newbie friendliness 35/100

UCL/rmcmc#128 · Opened Jul 6, 2026
Allow specifying models for target distribution using `brms` syntax Open

enhancement

Difficulty 5/5 Over a week Newbie friendliness 40/100

UCL/rmcmc#125 · Opened Jun 15, 2026
Proposal objects retain information about dimension first run with Open

enhancement

Difficulty 3/5 1-2 days Newbie friendliness 45/100

UCL/rmcmc#51 · Opened Dec 4, 2024
Support sampling multiple chains ideally with option for parallelizing Open

enhancement

Difficulty 5/5 Over a week Newbie friendliness 20/100

UCL/rmcmc#18 · 1 comment · Opened Jul 25, 2024

A short digest of beginner-friendly GitHub issues.