deGradInfer: Parameter Inference for Systems of Differential Equation

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

AuthorBenn Macdonald [aut], Frank Dondelinger [aut, cre]
MaintainerFrank Dondelinger <[email protected]>
LicenseGPL-3
Version1.0.0
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("deGradInfer")

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deGradInfer documentation built on Dec. 6, 2017, 1:03 a.m.