Clear/Set pipeline
.clearPipe(
rx = NULL,
inits = NULL,
events = NULL,
params = NULL,
iCov = NULL,
keep = NULL,
thetaMat = NULL,
omega = NULL,
sigma = NULL,
dfObs = NULL,
dfSub = NULL,
nSub = NULL,
nStud = NULL
)RxODE object
a vector of initial values of the state variables (e.g., amounts in each compartment), and the order in this vector must be the same as the state variables (e.g., PK/PD compartments);
an eventTable object describing the input
(e.g., doses) to the dynamic system and observation sampling
time points (see eventTable);
a numeric named vector with values for every parameter in the ODE system; the names must correspond to the parameter identifiers used in the ODE specification;
A data frame of individual non-time varying covariates
to combine with the params to form a parameter
data.frame.
Columns to keep from either the input dataset or the
iCov dataset. With the iCov dataset, the column
is kept once per line. For the input dataset, if any records
are added to the data LOCF (Last Observation Carried forward)
imputation is performed.
Named theta matrix.
Estimate of Covariance matrix. When omega is a list, assume it is a block matrix and convert it to a full matrix for simulations.
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.
Degrees of freedom to sample the unexplained variability matrix from the inverse Wishart distribution (scaled) or scaled inverse chi squared distribution.
Degrees of freedom to sample the between subject variability matrix from the inverse Wishart distribution (scaled) or scaled inverse chi squared distribution.
Number between subject variabilities (ETAs) simulated for every realization of the parameters.
Number virtual studies to characterize uncertainty in estimated parameters.