Parameters specified by the model

This returns the model's parameters that are required to solve the ODE system, and can be used to pipe parameters into an RxODE solve

rxParams(obj, ...)

# S3 method for RxODE
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, ...)

Arguments

obj	RxODE 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.
constants	is a boolean indicting if constants should be included in the list of parameters. Currently RxODE parses constants into variables in case you wish to change them without recompiling the RxODE model.
params	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;
inits	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);
iCov	A data frame of individual non-time varying covariates to combine with the events dataset by merge.
keep	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.
thetaMat	Named theta matrix.
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.
dfSub	Degrees of freedom to sample the between subject variability matrix from the inverse Wishart distribution (scaled) or scaled inverse chi squared distribution.
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.
dfObs	Degrees of freedom to sample the unexplained variability matrix from the inverse Wishart distribution (scaled) or scaled inverse chi squared distribution.
nSub	Number between subject variabilities (ETAs) simulated for every realization of the parameters.
nStud	Number virtual studies to characterize uncertainty in estimated parameters.

Value

When extracting the parameters from an RxODE model, a character vector listing the parameters in the model.

Author

Matthew L.Fidler