2009/07/24 by David J. Lunn, David J. Spiegelhalter, Andrew C. Thomas +1 · 4 citations
Computer Science · Mathematics · #Artificial intelligence #Bayesian Methods and Mixture Models #Bayesian inference #Bayesian probability #Computer science #Computer security #Data science #Econometrics #Economics #Flexibility (engineering) #Gaussian Processes and Bayesian Inference #Gibbs sampling #Inference #Mathematics #Principal (computer security) #Programming language #Raising (metalworking) #Software #Software bug #Software engineering #Statistical Methods and Bayesian Inference #Statistics
paper · doi:10.1002/sim.3680
openalex publication_date 2009/07/24 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/23
BUGS is a software package for Bayesian inference using Gibbs sampling. The software has been instrumental in raising awareness of Bayesian modelling among both academic and commercial communities internationally, and has enjoyed considerable success over its 20-year life span. Despite this, the software has a number of shortcomings and a principal aim of this paper is to provide a balanced critical appraisal, in particular highlighting how various ideas have led to unprecedented flexibility while at the same time producing negative side effects. We also present a historical overview of the BUGS project and some future perspectives.