WinBUGS – A Bayesian modelling framework: Concepts, structure, and extensibility

Authors:
David J. Lunn;Andrew Thomas;Nicky Best;David Spiegelhalter
Affiliations:
Department of Epidemiology and Public Health, Imperial College School of Medicine, Norfolk Place, London W2 1PG, UK. d.lunn@ic.ac.uk;Department of Epidemiology and Public Health, Imperial College School of Medicine, Norfolk Place, London W2 1PG, UK. a.thomas@ic.ac.uk;Department of Epidemiology and Public Health, Imperial College School of Medicine, Norfolk Place, London W2 1PG, UK. n.best@ic.ac.uk;Medical Research Council Biostatistics Unit, Institute of Public Health, Robinson Way, Cambridge CB2 2SR, UK. david.spiegelhalter@mrc-bsu.cam.ac.uk
Venue:
Statistics and Computing
Year:
2000

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Abstract

WinBUGS is a fully extensible modular framework for constructing and analysing Bayesian full probability models. Models may be specified either textually via the BUGS language or pictorially using a graphical interface called DoodleBUGS. WinBUGS processes the model specification and constructs an object-oriented representation of the model. The software offers a user-interface, based on dialogue boxes and menu commands, through which the model may then be analysed using Markov chain Monte Carlo techniques. In this paper we discuss how and why various modern computing concepts, such as object-orientation and run-time linking, feature in the software's design. We also discuss how the framework may be extended. It is possible to write specific applications that form an apparently seamless interface with WinBUGS for users with specialized requirements. It is also possible to interface with WinBUGS at a lower level by incorporating new object types that may be used by WinBUGS without knowledge of the modules in which they are implemented. Neither of these types of extension require access to, or even recompilation of, the WinBUGS source-code.