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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Detalles Bibliográficos
Autores principales: Pooley, C. M., Bishop, S. C., Doeschl-Wilson, A., Marion, G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society 2019
Materias:
Mathematics
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6894579/
https://www.ncbi.nlm.nih.gov/pubmed/31827823
http://dx.doi.org/10.1098/rsos.190619

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6894579/
https://www.ncbi.nlm.nih.gov/pubmed/31827823
http://dx.doi.org/10.1098/rsos.190619

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