seeds: Estimate Hidden Inputs using the Dynamic Elastic Net

Algorithms to calculate the hidden inputs of systems of differential equations. These hidden inputs can be interpreted as a control that tries to minimize the discrepancies between a given model and taken measurements. The idea is also called the Dynamic Elastic Net, as proposed in the paper "Learning (from) the errors of a systems biology model" (Engelhardt, Froelich, Kschischo 2016) <doi:10.1038/srep20772>. To use the experimental SBML import function, the 'rsbml' package is required. For installation I refer to the official 'rsbml' page: <https://bioconductor.org/packages/release/bioc/html/rsbml.html>.

Version:	0.9.1
Depends:	R (≥ 3.5.0)
Imports:	deSolve (≥ 1.20), pracma (≥ 2.1.4), Deriv (≥ 3.8.4), Ryacas, stats, graphics, methods, mvtnorm, matrixStats, statmod, coda, MASS, ggplot2, tidyr, dplyr, Hmisc, R.utils, callr
Suggests:	knitr, rmarkdown, rsbml
Published:	2020-07-14
DOI:	10.32614/CRAN.package.seeds
Author:	Tobias Newmiwaka [aut, cre], Benjamin Engelhardt [aut]
Maintainer:	Tobias Newmiwaka <tobias.newmiwaka at gmail.com>
BugReports:	https://github.com/Newmi1988/seeds/issues
License:	MIT + file LICENSE
URL:	https://github.com/Newmi1988/seeds
NeedsCompilation:	no
CRAN checks:	seeds results

Documentation:

Reference manual:	seeds.pdf
Vignettes:	Seeds: Calculating the hidden inputs in a system

Downloads:

Package source:	seeds_0.9.1.tar.gz
Windows binaries:	r-devel: seeds_0.9.1.zip, r-release: seeds_0.9.1.zip, r-oldrel: seeds_0.9.1.zip
macOS binaries:	r-release (arm64): seeds_0.9.1.tgz, r-oldrel (arm64): seeds_0.9.1.tgz, r-release (x86_64): seeds_0.9.1.tgz, r-oldrel (x86_64): seeds_0.9.1.tgz
Old sources:	seeds archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=seeds to link to this page.