The BUGS (Bayesian inference Using Gibbs
Sampling) project is concerned with flexible software
for the Bayesian analysis of complex statistical models using
Markov chain Monte Carlo (MCMC) methods. The project began in
1989 in the MRC Biostatistics Unit, Cambridge, and led initially to the `Classic' BUGS program,
and then onto the WinBUGS
software developed jointly with the Imperial College School of
Medicine at St Mary's, London.
Development is now focussed on the OpenBUGS project.
This site at the MRC Biostatistics Unit is primarily concerned with the stand-alone WinBUGS 1.4.3 package.
- Features a graphical user interface and on-line monitoring
and convergence diagnostics.
- Over 30000 downloads, and a huge number of applications and links.
- WinBUGS development site includes facilities to
add distributions, functions, and includes add-ons for pharmacokinetic modelling,
differential equations, and reversible jump MCMC.
- Can be called from R with R2WinBUGS.
WinBUGS 1.4.3 is a stable version which is recommended for standard use.
However many developments are now taking place using OpenBUGS.
Note: The preferred reference for citing WinBUGS in scientific papers is:
Lunn, D.J., Thomas, A., Best, N., and Spiegelhalter, D. (2000) WinBUGS -- a Bayesian modelling framework: concepts, structure, and extensibility. Statistics and Computing, 10:325--337.
project can be found here.
- Open-source version of the core BUGS code with a variety of interfaces.
- Runs under Windows with a very similar graphical interface to WinBUGS.
- Runs on Linux with a plain-text interface.
- Can be embedded in R as BRugs.
- Different architecture from WinBUGS 1.4.3: this means that WinBUGS 1.4
add-ons on the WinBUGS development site will not yet run in OpenBUGS.
OpenBUGS is the main development platform and is currently experimental,
but will eventually become the standard version. The aim is then to transfer new 1.4 functionality to
JAGS (Just Another Gibbs Sampler)
by Martyn Plummer is an open source program which was developed independently of the BUGS project.
JAGS uses essentially the same model description language, but it has been completely re-written.
This runs natively on Windows, Mac, Linux and several other varieties of Unix.
Independent corroboration of MCMC results is always valuable!
Stan is another program for general Bayesian analysis, developed even more recently at Columbia University. It uses a modelling language inspired by BUGS and superficially similar, but it is conceptually different in many ways.
The programs are reasonably easy to use and come with a wide range
of examples. There is, however, a need for caution. A knowledge of
Bayesian statistics is assumed, including recognition of the potential
importance of prior distributions, and MCMC is inherently less robust
than analytic statistical methods. There is no in-built protection