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
)rxode2 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 events dataset by merge.
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. When omega is NA and you are using it with a
rxode2 ui model, the between subject variability described by
the omega matrix are set to zero.
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. When sigma is NA and you are using it with a
rxode2 ui model, the unexplained variability described by
the sigma matrix are set to zero.
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.
None, clears rxode2 pipeline