Simulates data for multiple individuals in a mixed effects model based on stochastic differential equations using an euler scheme.
1  PSM.simulate(Model, Data, THETA, deltaTime, longX=TRUE)

Model 
A list containing the model components either Linear or NonLinear Model list.* 
Data 
List with elements described below. No

THETA 
Vector of population parameters 
deltaTime 
Time Step in the Euler scheme 
longX 
Boolean. Toggles output of the entire simulated outcome of the states 
* See description in PSM.estimate.
The eta is drawn from the multivariate normal distribution N(0,OMEGA). The simulation is an euler based method but for every time interval dt the model is predicted and the states affected by system noise (SIG).
The measurements are added an normal error term belonging to N(0,S).
The function mvrnorm
from the MASS pacakge is used to to
generate random numbers fra multivariate normal distributions.
The simulated outcome of the model is returned in a list, where each element is the data for an individual.
X 
Simulated states sampled at time points for measurements 
Y 
Simulated measurements 
Time 
Time points for measurements 
U 
Input vector used in the simulation 
eta 
The random effects used in the simulation 
Dose 
The dose list used in the simulation 
longX 
Entire outcome of simulated states 
longTime 
Time points for 
For further details please also read the package vignette pdfdocument
by writing vignette("PSM")
in R.
Stig B. Mortensen and S<f8>ren Klim
Please visit http://www.imm.dtu.dk/psm or refer to
the help page for PSM
.
PSM
, PSM.estimate
,
PSM.smooth
, PSM.plot
, PSM.template
1  cat("\nExamples are included in the package vignette.\n")

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