dMod: Dynamic Modeling and Parameter Estimation in ODE Models

The framework provides functions to generate ODEs of reaction networks, parameter transformations, observation functions, residual functions, etc. The framework follows the paradigm that derivative information should be used for optimization whenever possible. Therefore, all major functions produce and can handle expressions for symbolic derivatives. The methods used in dMod were published in Kaschek et al, 2019, <doi:10.18637/jss.v088.i10>.

Version: 1.0.2
Depends: cOde (≥ 1.0)
Imports: deSolve, rootSolve, ggplot2, parallel, stringr, plyr, dplyr, foreach, doParallel
Suggests: MASS, reticulate, pander, knitr, rmarkdown
Published: 2021-01-27
Author: Daniel Kaschek
Maintainer: Daniel Kaschek <daniel.kaschek at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Citation: dMod citation info
In views: DifferentialEquations
CRAN checks: dMod results

Documentation:

Reference manual: dMod.pdf
Vignettes: dMod

Downloads:

Package source: dMod_1.0.2.tar.gz
Windows binaries: r-devel: dMod_1.0.2.zip, r-release: dMod_1.0.2.zip, r-oldrel: dMod_1.0.2.zip
macOS binaries: r-release (arm64): dMod_1.0.2.tgz, r-release (x86_64): dMod_1.0.2.tgz, r-oldrel: dMod_1.0.2.tgz
Old sources: dMod archive

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