Package: deGradInfer
Title: Parameter Inference for Systems of Differential Equation
Version: 1.0.1
Authors@R: c(person("Benn", "Macdonald", email = "Benn.Macdonald@glasgow.ac.uk", role = c("aut")),
             person("Frank", "Dondelinger", email = "fdondelinger.work@gmail.com", role = c("aut", "cre")))
Description: 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.
Depends: R (>= 3.3.1)
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: deSolve, gdata, gptk, graphics, stats
RoxygenNote: 7.0.2
Suggests: testthat, knitr, rmarkdown, ggplot2
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-01-20 14:00:44 UTC; dondelin
Author: Benn Macdonald [aut],
  Frank Dondelinger [aut, cre]
Maintainer: Frank Dondelinger <fdondelinger.work@gmail.com>
Repository: CRAN
Date/Publication: 2020-01-20 19:30:25 UTC
Built: R 4.0.2; ; 2020-07-16 13:36:26 UTC; unix
