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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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| I publikationen: | R Soc Open Sci |
|---|---|
| Huvudupphovsmän: | , , , |
| Materialtyp: | Artigo |
| Språk: | Inglês |
| Publicerad: |
The Royal Society
2019
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| Ämnen: | |
| Länkar: | 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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