getPopulationElements
[Simulx] Get population parameters elements
Get the list of all available population parameters elements for the simulation. To use one of these elements in simulation, please add it to a simulation group with setGroupElement.
Usage
getPopulationElements()Details
Population parameters elements can be defined with definePopulationElement, or created at the import of a Monolix project with .importProject. Elements defined are created in the background and saved with the Simulx project if calling saveProject. They can be deleted with deleteElement
Each element is a list of
| "inputType" | (character) | Type of input definition: can be "manual", "distribution" or "external". |
| "file" | (list) | if the inputType is external, list with path to the file and sheet in the excel (if relevant) . NULL else wise. |
| "data" | (data.frame) | Values of the element. |
Notice that:
- if the project was created from a model file, a population element PopParameters is created with all values equal 1.
- if the project was created using by importing a Monolix project (with importProject),
a population element mlx_Pop is created with the population parameters estimated in the Monolix project.
if the parameters were not estimated in the Monolix project, a population element mlx_PopInit is created instead of mlx_Pop, with the initial values of the population parameters.
a population element mlx_PopUncertainSA (resp. mlx_PopUncertainLin) is created which enables to sample population parameters using the covariance matrix of the estimates computed by Monolix if the Standard Error task (Estimation of the Fisher Information matrix) was performed by stochastic approximation (resp. by linearization). To sample several population parameter sets, this element needs to be used with replicates (usesetNbReplicates.
a population element mlx_Typical is created with the population parameters estimated in the Monolix projects and all omega parameters set to zero. It is useful to simulate a typical individual with different covariate values than the reference in the model.
a population element mlx_TypicalUncertainSA (resp. mlx_TypicalUncertainLin) is created which is the same as mlx_PopUncertain but with all omegas set to zero to remove the inter-individual variability. It is useful to propagate the uncertainty of population parameters to the prediction of a typical individual.