createCompModel

a R-function that can be solved with deSolve. External input of the system should
be declared with 'u'. To ensure that the function is working use the most general
state-space representation.

modelFunc

a vector describing the parameters of the system. If names are missing the function
tries to extract the declared parameters from the model function.

parameters

a boolean that indicates if the c-file is used for the mcmc algorithm, default value is 'FALSE'

bden

a bit vector indicating the states that should be non negative

nnStates

Writes a c file that can be compiled for faster solution with the <code><a rd-options="deSolve" href="/link/ode?package=seeds&version=0.9.1&to=deSolve" data-mini-rdoc="deSolve::ode">ode</a></code> solver.
The file created is formatted to be used with the dynamic elastic net. A hidden input is 
added to every component of the state vector.

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>.

Tobias Newmiwaka

seeds

Estimate Hidden Inputs using the Dynamic Elastic Net

Benjamin Engelhardt

createCompModel function

Writes a c file that can be compiled for faster solution with the <code><a rd-options='deSolve' href='ode'>ode</a></code> solver.
The file created is formatted to be used with the dynamic elastic net. A hidden input is 
added to every component of the state vector.

createCompModel: Create compilable c-code of a model

Description

Usage

Arguments

Value