Estimate Hidden Inputs using the Dynamic Elastic Net


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Documentation for package ‘seeds’ version 0.9.1

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seeds-package seeds: Estimate Hidden Inputs using the Dynamic Elastic Net
BDEN Bayesian Dynamic Elastic Net
confidenceBands Get the estimated confidence bands for the bayesian method
confidenceBands-method Get the estimated confidence bands for the bayesian method
createCompModel Create compilable c-code of a model
DEN Greedy method for estimating a sparse solution
estiStates Get the estimated states
estiStates-method Get the estimated states
GIBBS_update Gibbs Update
hiddenInputs Get the estimated hidden inputs
hiddenInputs-method Get the estimated hidden inputs
importSBML Import SBML Models using the Bioconductor package 'rsbml'
LOGLIKELIHOOD_func Calculates the Log Likelihood for a new sample given the current state (i.e. log[L(G|x)P(G)])
MCMC_component Componentwise Adapted Metropolis Hastings Sampler
Model Test dataset for demonstrating the bden algorithm.
nominalSol Calculate the nominal solution of the model
nominalSol-method Calculate the nominal solution of the model
odeEquations A S4 class used to handle formatting ODE-Equation and calculate the needed functions for the seeds-algorithm
odeEquations-class A S4 class used to handle formatting ODE-Equation and calculate the needed functions for the seeds-algorithm
odeModel A class to store the important information of an model.
odeModel-class A class to store the important information of an model.
optimal_control_gradient_descent estimating the optimal control using the dynamic elastic net
outputEstimates Get the estimated outputs
outputEstimates-method Get the estimated outputs
plot-method Plot method for the S4 class resultsSeeds
plotAnno Create annotated plot
plotAnno-method Create annotated plot
print,resultsSeeds A default printing function for the resultsSeeds class
print-method A default printing function for the resultsSeeds class
res Results from the uvb dataset for examples
resultsSeeds Results Class for the Algorithms
resultsSeeds-class Results Class for the Algorithms
seeds seeds: Estimate Hidden Inputs using the Dynamic Elastic Net
setInitState Set the vector with the initial (state) values
setInitState-method Set the vector with the initial (state) values
setInput Set the inputs of the model.
setInput-method Set the inputs of the model.
setMeas set measurements of the model
setMeas-method set measurements of the model
setMeasFunc Set the measurement equation for the model
setMeasFunc-method Set the measurement equation for the model
setModelEquation Set the model equation
setModelEquation-method Set the model equation
setParms Set the model parameters
setParms-method Set the model parameters
setSd Set the standard deviation of the measurements
setSd-method Set the standard deviation of the measurements
SETTINGS Automatic Calculation of optimal Initial Parameters
uvbData UVB signal pathway
uvbModel An object of the odeModel Class