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A Language and Program for Complex Bayesian Modelling

W. R. Gilks, A. Thomas and D. J. Spiegelhalter
Journal of the Royal Statistical Society. Series D (The Statistician)
Vol. 43, No. 1, Special Issue: Conference on Practical Bayesian Statistics, 1992 (3) (1994), pp. 169-177
Published by: Wiley for the Royal Statistical Society
DOI: 10.2307/2348941
Stable URL: http://www.jstor.org/stable/2348941
Page Count: 9
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A Language and Program for Complex Bayesian Modelling
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Abstract

Gibbs sampling has enormous potential for analysing complex data sets. However, routine use of Gibbs sampling has been hampered by the lack of general purpose software for its implementation. Until now all applications have involved writing one-off computer code in low or intermediate level languages such as C or Fortran. We describe some general purpose software that we are currently developing for implementing Gibbs sampling: BUGS (Bayesian inference using Gibbs sampling). The BUGS system comprises three components: first, a natural language for specifying complex models; second, an 'expert system' for deciding appropriate methods for obtaining samples required by the Gibbs sampler: third, a sampling module containing numerical routines to perform the sampling. $S$ objects are used for data input and output. BUGS is written in Modula-2 and runs under both DOS and UNIX.

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