https://matt-graham.r-universe.devRecent package updates in matt-grahamR-universehttps://github.com/matt-graham.pnghttps://matt-graham.r-universe.devMon, 07 Sep 2026 13:34:54 GMTm.graham@ucl.ac.uk (Matthew M. Graham)Functions for simulating Markov chains to compute Markov chain Monte Carlo (MCMC) estimates of expectations with respect to a target distribution on a real-valued vector space. The package has built-in support for using Metropolis-Hastings transitions with random-walk, Langevin, Hamiltonian or Barker proposals, and is designed to be easy to extend with additional algorithms. Proposal shape and scale parameters can be automatically adapted in an initial warm-up stage. The package has a modular design allowing different algorithmic components such as proposals and adapters to be mixed and matched. If 'BridgeStan's R interface <https://roualdes.us/bridgestan/latest/languages/r.html>, available on GitHub <https://github.com/roualdes/bridgestan>, is installed, then it can be used to specify the target distribution to sample from.https://github.com/r-universe/ucl/actions/runs/37626074444Mon, 07 Sep 2026 13:34:54 GMTrmcmc0.1.2.9000successhttps://ucl.r-universe.devhttps://github.com/ucl/rmcmcadjusting-noise-distribution.Rmdadjusting-noise-distribution.htmlAdjusting the noise distribution in the Barker proposal2025-01-06 16:58:452025-02-17 16:30:06barker-proposal.Rmdbarker-proposal.htmlRobust gradient-based MCMC with the Barker proposal2024-10-14 15:24:412025-02-04 18:33:56