This returns the model's parameters that are required to solve the ODE system, and can be used to pipe parameters into an rxode2 solve
rxParams(obj, ...)# S3 method for rxode2
rxParams(
obj,
constants = TRUE,
...,
params = NULL,
inits = NULL,
iCov = NULL,
keep = NULL,
thetaMat = NULL,
omega = NULL,
dfSub = NULL,
sigma = NULL,
dfObs = NULL,
nSub = NULL,
nStud = NULL
)
# S3 method for rxSolve
rxParams(
obj,
constants = TRUE,
...,
params = NULL,
inits = NULL,
iCov = NULL,
keep = NULL,
thetaMat = NULL,
omega = NULL,
dfSub = NULL,
sigma = NULL,
dfObs = NULL,
nSub = NULL,
nStud = NULL
)
# S3 method for rxEt
rxParams(
obj,
...,
params = NULL,
inits = NULL,
iCov = NULL,
keep = NULL,
thetaMat = NULL,
omega = NULL,
dfSub = NULL,
sigma = NULL,
dfObs = NULL,
nSub = NULL,
nStud = NULL
)
rxParam(obj, ...)
rxode2 family of objects
Other arguments including scaling factors for each compartment. This includes S# = numeric will scale a compartment # by a dividing the compartment amount by the scale factor, like NONMEM.
is a boolean indicting if constants should be included in the list of parameters. Currently rxode2 parses constants into variables in case you wish to change them without recompiling the rxode2 model.
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 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);
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.
Degrees of freedom to sample the between subject variability matrix from the inverse Wishart distribution (scaled) or scaled inverse chi squared distribution.
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.
Number between subject variabilities (ETAs
) simulated for every
realization of the parameters.
Number virtual studies to characterize uncertainty in estimated parameters.
When extracting the parameters from an rxode2 model, a character vector listing the parameters in the model.
Other Query model information:
rxDfdy()
,
rxInits()
,
rxLhs()
,
rxModelVars()
,
rxState()