A comparison of approximate versus exact techniques for Bayesian parameter inference in nonlinear ordinary differential equation models

The behaviour of many processes in science and engineering can be accurately described by dynamical system models consisting of a set of ordinary differential equations (ODEs). Often these models have several unknown parameters that are difficult to estimate from experimental data, in which case Bay...

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Detalles Bibliográficos
Autores principales: Alahmadi, Amani A., Flegg, Jennifer A., Cochrane, Davis G., Drovandi, Christopher C., Keith, Jonathan M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society 2020
Materias:
Mathematics
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7137938/
https://www.ncbi.nlm.nih.gov/pubmed/32269786
http://dx.doi.org/10.1098/rsos.191315

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7137938/
https://www.ncbi.nlm.nih.gov/pubmed/32269786
http://dx.doi.org/10.1098/rsos.191315

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