generate.data.maillard: Maillard reaction
In CausalKinetiX: Learning Stable Structures in Kinetic Systems

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.

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. `noise.sd` specifies the standard deviation of noise, `only.target.noise` specifies whether to only add noise to target and `relative` specifies if the size of the noise should be relative to size of variable (if TRUE standard deviation is given by par.noise$noise.sd*(x(t)-x(t-1))).
`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 `deSolve` package ("lsoda", "lsode", "lsodes", "lsodar", "vode", "daspk", "euler", "rk4", "ode23", "ode45", "radau", "bdf", "bdf_d", "adams", "impAdams", "impAdams_d", "iteration").
`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.

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))