create_ModelEmax {Certara.RDarwin} | R Documentation |
Get the list of objects describing the PML models by set of Emax parameters
Description
This function provides the PML (Pharmacometric Modelling Language) Emax parameter sets based on the specified options. They are available as a list of specific S3 classes.
Usage
create_ModelEmax(
Baseline = FALSE,
Fractional = FALSE,
Inhibitory = FALSE,
Sigmoid = FALSE,
ByVector = FALSE,
...
)
Arguments
Baseline |
Logical indicating whether the Emax model contains a baseline
response. If it is set to TRUE, the new parameter, E0, for baseline
response is added to the model. Default is |
Fractional |
Logical indicating whether the Emax model with baseline
response is fractional. Applicable only for the Emax models with baseline
response, otherwise a warning is given and current parameter is ignored.
Default is |
Inhibitory |
Logical indicating whether the model is inhibitory. If it
is set to TRUE, the structural parameters 'EC50' and 'Emax' change to
'IC50' (concentration producing 50% of maximal inhibition) and 'Imax'.
Default is |
Sigmoid |
Logical indicating whether the model is sigmoidal. If it is
set to TRUE, the Hill coefficient, 'Gam', is added to the model. Default is
|
ByVector |
Logical indicating whether each element in vectorized
argument should be treated as a separate PML structure (i.e. treated as
data.frame vectors), |
... |
Additional named arguments, including Structural parameters (StParm), Covariates, Dosepoints (for PK models), Thetas and Omegas. See 'Additional arguments' section. |
Value
A list of PML models (PMLModels
class instance) matching the
specified options.
Examples
# Get Emax model set with default options
PDParametersSets <- create_ModelEmax()
# Create Emax model set with all possible combinations
# will give a warning since When 'Baseline == FALSE',
# there could be no model with 'Fractional == TRUE'
PDParametersSets <-
create_ModelEmax(Baseline = TRUE,
Fractional = c(FALSE, TRUE),
Inhibitory = c(FALSE, TRUE),
Sigmoid = c(FALSE, TRUE),
ByVector = FALSE)