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Posterior-based proposals for speeding up Markov chain Monte Carlo

Markov chain Monte Carlo (MCMC) is widely used for Bayesian inference in models of complex systems. Performance, however, is often unsatisfactory in models with many latent variables due to so-called poor mixing, necessitating the development of application-specific implementations. This paper intro...

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Veröffentlicht in:R Soc Open Sci
Hauptverfasser: Pooley, C. M., Bishop, S. C., Doeschl-Wilson, A., Marion, G.
Format: Artigo
Sprache:Inglês
Veröffentlicht: The Royal Society 2019
Schlagworte:
Online Zugang:https://ncbi.nlm.nih.gov/pmc/articles/PMC6894579/
https://ncbi.nlm.nih.gov/pubmed/31827823
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1098/rsos.190619
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