| PSM.simulate {PSM} | R Documentation |
Simulates data for multiple individuals in a mixed effects model based on stochastic differential equations using an euler scheme.
PSM.simulate(Model, Data, THETA, deltaTime, longX=TRUE)
Model |
A list containing the model components either Linear or Non-Linear Model list.* |
Data |
List with elements described below. No Data$Y is needed as it
is generated through the simulation. The number of individuals
simulated is equal to length(Data).
|
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 longX.
|
For further details please also read the package vignette pdf-document by writing vignette("PSM") in R.
Stig B. Mortensen and Søren 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
cat("\nExamples are included in the package vignette.\n")