Efficient Bayesian parameter inference for systems of ordinary differential equations. The inference is based on adaptive gradient matching (AGM, Dondelinger et al. 2013 <http://proceedings.mlr.press/v31/dondelinger13a.pdf>, Macdonald 2017 <http://theses.gla.ac.uk/7987/1/2017macdonaldphd.pdf>), which offers orders-of-magnitude improvements in computational efficiency over standard methods that require solving the differential equation system. Features of the package include flexible specification of custom ODE systems as R functions, support for missing variables, Bayesian inference via population MCMC.
Package details |
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Author | Benn Macdonald [aut], Frank Dondelinger [aut, cre] |
Maintainer | Frank Dondelinger <fdondelinger.work@gmail.com> |
License | GPL-3 |
Version | 1.0.1 |
Package repository | View on CRAN |
Installation |
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