ArticleJournal of statistical software2020
MultiBUGS: A Parallel Implementation of the BUGS Modelling Framework for Faster Bayesian Inference.
Article in Journal of statistical software, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.
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Who cites it
22 citing papers in PubMed, 1 synthesis or guideline pooled it.
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- Single-Photon Single-Particle Tracking.bioRxiv : the preprint server for biology · 2025Article
- How Does the Interaction Between Preterm Delivery and Low Birthweight Contribute to Racial Disparity in Infant Mortality in the United States?Journal of clinical medicine · 2025Article
- Comparative effectiveness of manual therapy, pharmacological treatment, exercise therapy, and education for neck pain (COMPETE study): protocol of a systematic review with network meta-analysis.Systematic reviews · 2025Article
- Bayesian mediation modeling of racial disparity for maternal birth outcomes in United States.Medical research archives · 2024Article
- Mediation Analysis of Racial Disparity for Infant Mortality Using Bayesian Estimation of Potential Outcomes.Journal of clinical medicine · 2024Article
- Reliable event rates for disease mapping.Journal of official statistics · 2024Article
- Bayesian Spatio-Temporal Multilevel Modelling of Patient-Reported Quality of Life following Prostate Cancer Surgery.Healthcare (Basel, Switzerland) · 2024Article
- Incidence of typhoid fever in Burkina Faso, Democratic Republic of the Congo, Ethiopia, Ghana, Madagascar, and Nigeria (the Severe Typhoid in Africa programme): a population-based study.The Lancet. Global health · 2024Article
- Vector time series modelling of turbidity in Dublin Bay.Journal of applied statistics · 2024Article
- Use of second-generation antipsychotics in autism spectrum disorder: a systematic review and meta-analysis protocol.BMJ open · 2023Article
- A Bayesian approach to differential edges with probabilistic interactions: applications in association and classification.Bioinformatics advances · 2023Article
- More future synergies and less trade-offs between forest ecosystem services with natural climate solutions instead of bioeconomy solutions.Global change biology · 2022Article
- Scalable proximal methods for cause-specific hazard modeling with time-varying coefficients.Lifetime data analysis · 2022Article
- Forecasting of Lung Cancer Incident Cases at the Small-Area Level in Victoria, Australia.International journal of environmental research and public health · 2021Article
- The Effects of Parent Ages on Birth Defects.Acta scientific paediatrics · 2020Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
MultiBUGS is a new version of the general-purpose Bayesian modelling software BUGS that implements a generic algorithm for parallelising Markov chain Monte Carlo (MCMC) algorithms to speed up posterior inference of Bayesian models. The algorithm parallelises evaluation of the product-form likelihoods formed when a parameter has many children in the directed acyclic graph (DAG) representation; and parallelises sampling of conditionally-independent sets of parameters. A heuristic algorithm is used to decide which approach to use for each parameter and to apportion computation across computational cores. This enables MultiBUGS to automatically parallelise the broad range of statistical models that can be fitted using BUGS-language software, making the dramatic speed-ups of modern multi-core computing accessible to applied statisticians, without requiring any experience of parallel programming. We demonstrate the use of MultiBUGS on simulated data designed to mimic a hierarchical e-health linked-data study of methadone prescriptions including 425,112 observations and 20,426 random effects. Posterior inference for the e-health model takes several hours in existing software, but MultiBUGS can perform inference in only 28 minutes using 48 computational cores.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.