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brew

Install jags with Homebrew, apt, MacPorts, Nix

Just Another Gibbs Sampler for Bayesian MCMC simulation. Version 4.3.2 via Homebrew; verified from local package data.

install

Additional install commands

macOS

Homebrewverified · 100%
brew install jags

local Homebrew formula metadata

MacPortsverified · 94%
sudo port install jags

MacPorts ports tree · science/jags/Portfile · source: api.github.com

Linux

Debian aptverified · 92%
sudo apt install jags

Debian stable package indexes · jags · source: deb.debian.org

Nixverified · 92%
nix profile install nixpkgs#jags

nixpkgs package indexes · pkgs/by-name/ja/jags/package.nix · source: api.github.com

overview

Package summary

Just Another Gibbs Sampler for Bayesian MCMC simulation

Commands and aliases

  • jags

history

Project history and usage

JAGS, Just Another Gibbs Sampler, is a Bayesian MCMC engine for models written in the BUGS language family. Its package-manager role is to provide the native sampler executable and library that statistical front ends, especially R interfaces, can call.

Project history

Martyn Plummer presented JAGS at the 2003 Distributed Statistical Computing workshop as a program for Bayesian graphical models using Gibbs sampling, aiming at compatibility with classic BUGS while leaving room for an R package interface. The project site later summarized the same design goals as a cross-platform BUGS engine, an extensible system for custom functions, distributions, and samplers, and a platform for Bayesian modelling experiments.

The SourceForge project became the authoritative home for source, manuals, and binaries. Its code tree identifies JAGS as a C++ implementation based on the BUGS program created by the MRC Biostatistics Unit, and the project site documents binary distribution for macOS and Windows plus separate Debian, Ubuntu, and MacPorts packaging.

Adoption history

JAGS adoption is closely tied to the BUGS ecosystem and to R. The project site explicitly points users to Debian, Ubuntu, and MacPorts packages, while the rjags documentation describes an interface to the JAGS MCMC library maintained by Martyn Plummer. Homebrew API data available during this enrichment recorded 890 installs over 365 days, which is small compared with broad CLI tools but meaningful for a specialized scientific engine.

The package has persisted because it gives statisticians a scriptable, cross-platform BUGS-language engine without depending on the WinBUGS/OpenBUGS GUI tradition. That made it a practical backend for teaching, ecological models, Bayesian hierarchical workflows, and R-driven analysis pipelines.

How it is used

Users write Bayesian hierarchical models in a BUGS-like language, run MCMC simulation through the `jags` terminal interface or an integration such as rjags, and post-process chains in statistical software. The package is a computation backend rather than a general-purpose interactive application.

Why package nerds care

JAGS is package-nerd interesting because it is a long-lived SourceForge-era scientific tool that still matters at the package boundary: install the native sampler once, then R, scripts, courses, and reproducible analyses can target the same engine across Unix-like systems, Windows, and macOS.

Timeline

  • 2003: Plummer's DSC paper described JAGS as a BUGS-compatible Bayesian graphical modelling program.
  • 2015: JAGS 4.0.0 NEWS recorded language and library changes including log-density functions, vector indexing, additional distributions, and better compiler diagnostics.
  • 2022: JAGS 4.3.1 NEWS recorded a Windows installer update for the Rtools42 toolchain.
  • 2023: The project site recorded JAGS 4.3.2 as released on March 4, 2023, and the JAGS News post described it as a patch release for evolving C++ standard requirements.
  • 5.0.0: The NEWS file records new monitor types for deviance-related summaries and WAIC-oriented workflows.

Related projects

  • JAGS belongs to the BUGS lineage with WinBUGS, OpenBUGS, and MultiBUGS, and it is commonly paired with R packages such as rjags. It is conceptually adjacent to later Bayesian engines such as Stan, but its historical niche is BUGS-language compatibility and Gibbs-sampling-oriented extensibility.

security posture

Risk level: green

narrow executable package without higher-risk signals.

Risk classifier

green risk · low confidence · appliance

Why

  • narrow executable package without higher-risk signals

Signals

  • metadata:no-higher-risk-signals

Install behavior

  • No Homebrew post-install hook is recorded in formula metadata.
  • Homebrew bottle metadata is available for 8 platform targets.
  • Installs with 1 runtime dependencies.
  • Build metadata lists 1 build dependencies.

Recommended review

Before unattended agent use, check whether the tool reads plaintext credentials, writes remote state, publishes artifacts, or shells out to plugins.

executables

Installed executables

CommandKindExposureNote
jagscliglobal executable

freshness

Version and freshness

These signals separate page generation age, package-manager activity, and upstream release comparison. Version lag is warned only when an evidence URL and comparable versions are present.

page generated2026-07-08
manager version4.3.2
manager updated
local dataok
upstreamnot checked
latest detectednot detected

https://mcmc-jags.sourceforge.io

  • infoNo package-manager update timestamp was available.low confidence
  • infoRelease/tag comparison is only available for GitHub repositories.https://mcmc-jags.sourceforge.ionone confidence

install metadata

Package metadata

Package keybrew:jags
Version4.3.2
Package managerHomebrew
Package manager pagehttps://formulae.brew.sh/formula/jags
Homepagehttps://mcmc-jags.sourceforge.io
Repositoryhttps://sourceforge.net/p/mcmc-jags/code-0/ci/default/tree
Upstream docshttps://sourceforge.net/projects/mcmc-jags/files/Manuals/4.x
LicenseGPL-2.0-only
Source archivehttps://downloads.sourceforge.net/project/mcmc-jags/JAGS/4.x/Source/JAGS-4.3.2.tar.gz
Dependenciesopenblas
Build dependenciesgcc
Bottleavailable (on arm64_linux, arm64_sequoia, arm64_sonoma, arm64_tahoe, arm64_ventura, sonoma, ventura, x86_64_linux)
Homebrew post-installnot defined
Servicenone declared

registry facts

Source database details

Source DatabaseHomebrew formula API
Taphomebrew/core
Full Namejags
Version Scheme0
Revision0
Bottle Stable Root URLhttps://ghcr.io/v2/homebrew/core
Deprecatedno
Disabledno
Keg Onlyno
URL Keys
  • stable

source database matches

Other package-manager records

Matches are pulled from external package-manager indexes and kept separate from local Automic Vault package links.

Debian apt95%

jags 4.3.2-1

Just Another Gibbs Sampler for Bayesian MCMC - binary

https://mcmc-jags.sourceforge.io

sudo apt install jags
  • Section: math
  • Architecture: amd64
  • 8 dependencies
  • normalized package name match
  • Matched by: Jags
Debian stable package indexes · deb.debian.org · Debian stable package indexes: jags from https://deb.debian.org/debian/dists/stable/main/binary-amd64/Packages.xz
Nix95%

jags

nix profile install nixpkgs#jags
  • normalized package name match
  • Matched by: Jags
nixpkgs package indexes · api.github.com · nixpkgs package indexes: pkgs/by-name/ja/jags/package.nix from https://api.github.com/repos/NixOS/nixpkgs/git/trees/master?recursive=1
Ubuntu apt95%

jags 4.3.2-1

Just Another Gibbs Sampler for Bayesian MCMC - binary

https://mcmc-jags.sourceforge.io

sudo apt install jags
  • Section: universe/math
  • Architecture: amd64
  • 8 dependencies
  • normalized package name match
  • Matched by: Jags
Ubuntu 24.04 LTS package indexes · archive.ubuntu.com · Ubuntu 24.04 LTS package indexes: jags from https://archive.ubuntu.com/ubuntu/dists/noble/universe/binary-amd64/Packages.gz
MacPorts95%

jags

sudo port install jags
  • normalized package name match
  • Matched by: Jags
MacPorts ports tree · api.github.com · MacPorts ports tree: science/jags/Portfile from https://api.github.com/repos/macports/macports-ports/git/trees/master?recursive=1

source trail

Generated from repository data

This page is generated by av-web from the private package SQLite artifact built by scripts/generate-pkg-sqlite.py.

Used sources

  • Geiger risk classifier
  • Nucleus package database
  • av.db category and tag curation
  • cross-ecosystem install command graph
  • curated package history
  • external package-manager database matches
  • package relationship graph
  • package version freshness
  • package-page enrichment