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An efficient interpolation technique for jump proposals in reversible-jump Markov chain Monte Carlo calculations

Selection among alternative theoretical models given an observed dataset is an important challenge in many areas of physics and astronomy. Reversible-jump Markov chain Monte Carlo (RJMCMC) is an extremely powerful technique for performing Bayesian model selection, but it suffers from a fundamental d...

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Detalles Bibliográficos
Autores principales: Farr, W. M., Mandel, I., Stevens, D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society Publishing 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4632544/
https://www.ncbi.nlm.nih.gov/pubmed/26543580
http://dx.doi.org/10.1098/rsos.150030