Description Usage Arguments Details Value Author(s) References See Also Examples
Generate sample data from the Maillard reaction as specified by Bio52 in the BioModel data base.
1 2 3 4 | generate.data.maillard(target, env = rep(1, 10), L = 15,
par.noise = list(noise.sd = 0.01, only.target.noise = FALSE, relativ =
FALSE), intervention = "initial_blockreactions",
ode.solver = "lsoda", seed = NA, silent = FALSE)
|
target |
specifies which species is used as a target, needs to be an integer between 1 and 11. |
env |
integer vector of length n encoding to which experiment each repetition belongs. |
L |
number of time points for evaluation. |
par.noise |
list of parameters that specify the added
noise. |
intervention |
string specifying type of intervention. Currently three type of interventions are implemented "initial" (only intervene on intial values), "blockreactions" (intervene by blocking random reactions) or "intial_blockreactions" (intervene on both initial values and blockreactions"). |
ode.solver |
specifies which ODE solver to use when solving
ODE. Should be one of the methods from the |
seed |
random seed. Does not work if a "Detected blow-up" warning shows up. |
silent |
set to TRUE if no status output should be produced. |
For further details see the references.
list consisting of the following elements
simulated.data |
D-matrix of noisy data. |
time |
vector containing time points |
env |
vector specifying the experimental environment. |
simulated.model |
object returned by ODE solver. |
true.model |
vector specifying the target equation model. |
target |
target variable. |
Niklas Pfister, Stefan Bauer and Jonas Peters
Pfister, N., S. Bauer, J. Peters (2018). Identifying Causal Structure in Large-Scale Kinetic Systems ArXiv e-prints (arXiv:1810.11776).
Brands C. and van Boekel M. (2002). Kinetic modeling of reactions in heated monosaccharide-casein systems. Journal of agricultural and food chemistry, 50(23):6725–6739.
The functions generate.data.hidden
and
generate.data.targetmodel
allow to simulate ODE data
from two additional models.
1 2 3 4 5 6 7 8 9 10 11 12 | simulation.obj <- generate.data.maillard(target=1,
env=rep(1:5, 3),
L=15)
D <- simulation.obj$simulated.data
fulldata <- simulation.obj$simulated.model
time <- simulation.obj$time
plot(fulldata[[1]][,1], fulldata[[1]][,2], type= "l", lty=2,
xlab="time", ylab="concentration")
points(time, D[1,1:length(time)], col="red", pch=19)
legend("topright", c("true trajectory", "observations"),
col=c("black", "red"), lty=c(2, NA), pch=c(NA, 19))
|
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