rxParams function

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 rxode2 solve

rxParams(obj, ...)

## S3 method for class '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 class '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 class '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: 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.
• constants: 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.
• 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. The iCov dataset has one covariate per ID and should match the event table
• 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. 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.
• 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. 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.
• 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.

Returns

When extracting the parameters from an rxode2 model, a character vector listing the parameters in the model.

See Also

Other Query model information: rxDfdy(), rxInits(), rxLhs(), rxModelVars(), rxState()

Author(s)

Matthew L.Fidler