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arXiv · 1607.06779

Joining and splitting models with Markov melding

Robert J. B. Goudie·Anne M. Presanis·David Lunn·Daniela De Angelis·Lorenz Wernisch
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Abstract

Analysing multiple evidence sources is often feasible only via a modular approach, with separate submodels specified for smaller components of the available evidence. Here we introduce a generic framework that enables fully Bayesian analysis in this setting. We propose a generic method for forming a suitable joint model when joining submodels, and a convenient computational algorithm for fitting this joint model in stages, rather than as a single, monolithic model. The approach also enables splitting of large joint models into smaller submodels, allowing inference for the original joint model to be conducted via our multi-stage algorithm. We motivate and demonstrate our approach through two examples: joining components of an evidence synthesis of A/H1N1 influenza, and splitting a large ecology model.

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Robert J. B. Goudie, Anne M. Presanis, David Lunn, Daniela De Angelis, Lorenz Wernisch. 2016-07-22. Joining and splitting models with Markov melding. https://doi.org/10.1214/18-ba1104

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