No. 106 of 106 ·Statistical Analysis Software

rmcmc

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Freedom report

No signalScore 4.6

Free tierNo free tier on record
Open codeNo open-source code on record
Runs widely0 of 6 device platforms
DocumentedThinly documented

rmcmc is ranked #106 of 106 in statistical analysis software on Freedom251.

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The record

Purpose: rmcmc is an R package for simulating Markov chains to compute MCMC estimates of expectations for target distributions on real-valued vector spaces.
Sampling methods: It supports Metropolis-Hastings transitions with random-walk, Langevin, Hamiltonian, and Barker proposals; Barker is the default.
Warm-up adaptation: During warm-up, adapters can tune proposal scale and shape.
Target distributions: The sampling function accepts a log-density formula, a list of density and gradient functions, or a BridgeStan StanModel when BridgeStan is installed.
Stan integration: The package can use Stan models through BridgeStan’s R interface when that interface is installed.
Other integrations: The site says ramcmc can provide robust adaptive Metropolis proposal adaptation, and generated chain output can be passed to posterior summary and convergence-diagnostic functions.
Output: Sampling returns the final chain state, main-iteration traces, and transition statistics; warm-up traces and statistics are available when trace_warm_up is enabled.
Installation: The site gives CRAN installation with install.packages("rmcmc") and GitHub installation for the development version.
License: The site identifies the package license as MIT.
Support: The site links to GitHub issues for bug reports and provides a contributing guide and code of conduct.
Intended use: The package is for users who want to define a target distribution and sample a Markov chain, with a documented example fitting a model to neuroscience data using Stan.

Where it ranks on Freedom251

Best Statistical Analysis Software in 2026#106 of 106

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Sources

github-pages.ucl.ac.uk/rmcmc/· checked 5 Oct 2026
github-pages.ucl.ac.uk/rmcmc/reference/sample_chain.html· checked 5 Oct 2026
github-pages.ucl.ac.uk/rmcmc/articles/interfacing-with-stan-mo· checked 5 Oct 2026