[Monolix] Set population parameters initialization and estimation method
Set the initial value, the estimation method and, if relevant, the MAP parameters of one or more of the population parameters present within the current project. This includes fixed effects, random effects, error model, covariate, and correlation parameters.
Usage
setPopulationParameterInformation(...)
Arguments
... A set of comma-separated lists, where any omitted list entry will remain unchanged paramName = list( initialValue = (double), method = (character) "method" ). (See Details for additional list entries for the MAP method)
Details
Available estimation methods are:
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Fixed parameter |
No estimation |
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Maximum Likelihood Estimation |
SAEM algorithm |
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Maximum A Posteriori Estimation |
Bayesian estimation |
Call getPopulationParameterInformation to get a list of the initializable population parameters present within the current project.
For the "MAP" estimation method, the user can specify the associated typical value and standard deviation values by using additional list elements:
paramName = list( initialValue = (double), method = "MAP", priorValue = (double), priorSD = (double) )
By default, the prior value corresponds to the the population parameter and the prior standard deviation is set to 1. See example.
See also
getPopulationParameterInformation to get the population parameter information
setInitialEstimatesToLastEstimates to set the population parameter initial values to the last estimated values
getFixedEffectsByAutoInit to estimate initial values for the population parameters which can be passed to this method
Examples
initializeLixoftConnectors("monolix")
loadProject(file.path(getDemoPath(), "1.creating_and_using_models", "1.1.libraries_of_models", "theophylline_project.mlxtran"))
setPopulationParameterInformation(Cl_pop = list(initialValue = 0.5, method = "FIXED"),
V_pop = list(initialValue = 1),
ka_pop = list(method = "MAP", priorValue = 1, priorSD = 0.1))
getPopulationParameterInformation()
#> name initialValue method priorValue priorSD
#> 1 ka_pop 1.0 MAP 1 0.1
#> 2 V_pop 1.0 MLE NA NA
#> 3 Cl_pop 0.5 FIXED NA NA
#> 4 omega_Cl 1.0 MLE NA NA
#> 5 omega_V 1.0 MLE NA NA
#> 6 omega_ka 1.0 MLE NA NA
#> 7 a 1.0 MLE NA NA
#> 8 b 0.3 MLE NA NA
#> 9 c 1.0 FIXED NA NA