simTs: Simulate a model on a regular grid of times, using a function...
In smfsb: Stochastic Modelling for Systems Biology

Description Usage Arguments Value See Also Examples

This function simulates single realisation of a model on a regular grid of times using a function (closure) for advancing the state of the model, such as created by StepGillespie or StepEulerSPN.

1	simTs(x0,t0=0,tt=100,dt=0.1,stepFun,...)

`x0`	The initial state of the process at time `t0`.
`t0`	The initial time to be associated with the initial state `x0`. Defaults to 0.
`tt`	The terminal time of the simulation.
`dt`	The time step of the output. Note that this time step relates only to the recorded output, and has no bearing on the accuracy of the simulation process.
`stepFun`	A function (closure) for advancing the state of the process, such as produced by `StepGillespie` or `StepEulerSPN`.
`...`	Additional arguments will be passed to `stepFun`.

An R ts object representing the simulated process.

StepEulerSPN, StepGillespie, StepSDE, simTimes, simSample, as.timedData

# load the LV model
data(spnModels)
# create a stepping function
stepLV = StepGillespie(LV)
# simulate a realisation of the process and plot it
out = simTs(c(x1=50,x2=100),0,100,0.1,stepLV)
plot(out)
plot(out,plot.type="single",lty=1:2)