Simulate Parameters from a Theta/Omega specification
rxSimThetaOmega(
params = NULL,
omega = NULL,
omegaDf = NULL,
omegaLower = as.numeric(c(R_NegInf)),
omegaUpper = as.numeric(c(R_PosInf)),
omegaIsChol = FALSE,
omegaSeparation = "auto",
omegaXform = 1L,
nSub = 1L,
thetaMat = NULL,
thetaLower = as.numeric(c(R_NegInf)),
thetaUpper = as.numeric(c(R_PosInf)),
thetaDf = NULL,
thetaIsChol = FALSE,
nStud = 1L,
sigma = NULL,
sigmaLower = as.numeric(c(R_NegInf)),
sigmaUpper = as.numeric(c(R_PosInf)),
sigmaDf = NULL,
sigmaIsChol = FALSE,
sigmaSeparation = "auto",
sigmaXform = 1L,
nCoresRV = 1L,
nObs = 1L,
dfSub = 0,
dfObs = 0,
simSubjects = TRUE
)
params | Named Vector of RxODE model parameters |
---|---|
omega | Estimate of Covariance matrix. When omega is a list, assume it is a block matrix and convert it to a full matrix for simulations. |
omegaDf | The degrees of freedom of a t-distribution for
simulation. By default this is |
omegaLower | Lower bounds for simulated ETAs (by default -Inf) |
omegaUpper | Upper bounds for simulated ETAs (by default Inf) |
omegaIsChol | Indicates if the |
omegaSeparation | Omega separation strategy Tells the type of separation strategy when
simulating covariance with parameter uncertainty with standard
deviations modeled in the
|
omegaXform | When taking
|
nSub | Number between subject variabilities ( |
thetaMat | Named theta matrix. |
thetaLower | Lower bounds for simulated population parameter
variability (by default |
thetaUpper | Upper bounds for simulated population unexplained
variability (by default |
thetaDf | The degrees of freedom of a t-distribution for
simulation. By default this is |
thetaIsChol | Indicates if the |
nStud | Number virtual studies to characterize uncertainty in estimated parameters. |
sigma | Named sigma covariance or Cholesky decomposition of a covariance matrix. The names of the columns indicate parameters that are simulated. These are simulated for every observation in the solved system. |
sigmaLower | Lower bounds for simulated unexplained variability (by default -Inf) |
sigmaUpper | Upper bounds for simulated unexplained variability (by default Inf) |
sigmaDf | Degrees of freedom of the sigma t-distribution. By
default it is equivalent to |
sigmaIsChol | Boolean indicating if the sigma is in the Cholesky decomposition instead of a symmetric covariance |
sigmaSeparation | separation strategy for sigma; Tells the type of separation strategy when
simulating covariance with parameter uncertainty with standard
deviations modeled in the
|
sigmaXform | When taking
|
nCoresRV | Number of cores used for the simulation of the sigma variables. By default this is 1. To reproduce the results you need to run on the same platform with the same number of cores. This is the reason this is set to be one, regardless of what the number of cores are used in threaded ODE solving. |
nObs | Number of observations to simulate (with |
dfSub | Degrees of freedom to sample the between subject variability matrix from the inverse Wishart distribution (scaled) or scaled inverse chi squared distribution. |
dfObs | Degrees of freedom to sample the unexplained variability matrix from the inverse Wishart distribution (scaled) or scaled inverse chi squared distribution. |
simSubjects | boolean indicated RxODE should simulate subjects in studies ( |
a data frame with the simulated subjects
Matthew L.Fidler