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Bayesian inference using Gibbs sampling (BUGS) is a
statistical software Statistical software are specialized computer programs for analysis in statistics and econometrics. Open-source * ADaMSoft – a generalized statistical software with data mining algorithms and methods for data management * ADMB – a softwa ...
for performing Bayesian inference using
Markov chain Monte Carlo In statistics, Markov chain Monte Carlo (MCMC) methods comprise a class of algorithms for sampling from a probability distribution. By constructing a Markov chain that has the desired distribution as its equilibrium distribution, one can obtain ...
(MCMC) methods. It was developed by
David Spiegelhalter Sir David John Spiegelhalter (born 16 August 1953) is a British statistician and a Fellow of Churchill College, Cambridge. From 2007 to 2018 he was Winton Professor of the Public Understanding of Risk in the Statistical Laboratory at the Un ...
at the Medical Research Council Biostatistics Unit in
Cambridge Cambridge ( ) is a university city and the county town in Cambridgeshire, England. It is located on the River Cam approximately north of London. As of the 2021 United Kingdom census, the population of Cambridge was 145,700. Cambridge beca ...
in 1989 and released as free software in 1991. The BUGS project has evolved through four main versions: ClassicBUGS, WinBUGS, OpenBUGS an
MultiBUGS
MultiBUGS is built on the existing algorithms and tools in OpenBUGS and WinBUGS, which are no longer developed, and implements
parallelization Parallel computing is a type of computation in which many calculations or processes are carried out simultaneously. Large problems can often be divided into smaller ones, which can then be solved at the same time. There are several different f ...
to speed up computation. Several R packages are available
R2MultiBUGS
acts as an interface to MultiBUGS, whil
Nimble
is an extension of the BUGS language. Alternative implementations of the BUGS language include JAGS and Stan.


See also

* Spike and slab variable selection *
Bayesian structural time series Bayesian structural time series (BSTS) model is a statistical technique used for feature selection, time series forecasting, nowcasting, inferring causal impact and other applications. The model is designed to work with time series data. The mod ...


References


External links


The BUGS Project
Computational statistics Domain-specific programming languages {{statistics-stub