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Description of the R functions associated to the population parameters

Description of the functions of the API

getFixedEffectsByAutoInit Compute optimized values for initial population parameters.
getPopulationParameterInformation Get the name, the initial value, the estimation method and, if relevant, MAP parameters value of the population parameters present in the project.
setInitialEstimatesToLastEstimates Set the initial value of all the population parameters present within the current project to the ones previously estimated.
setPopulationParameterInformation Set the initial value, the estimation method and, if relevant, the MAP parameters of one or several of the population parameters present within the current project (fixed effects + individual variances + error model parameters).

[Monolix] Automatically estimate initial parameters value

Description

Compute optimized values for initial population parameters. The values are returned in the same format as the entry, and can be then used to run the method again.

Usage

getFixedEffectsByAutoInit(parameters)

Arguments

parameters (data.frame), in the same format as the one returned by getPopulationParameterInformation.

Click here to see examples

getPopulationParameterInformation() -> parameters

getFixedEffectsByAutoInit(parameters) -> optimizedParameters

## End(Not run)


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[Monolix] Get population parameters information

Description

Get the name, the initial value, the estimation method and, if relevant, MAP parameters value of the population parameters present in the project.
It is available for fixed effects, random effects, error model parameters, and latent covariates probabilities.

Usage

getPopulationParameterInformation()

Value

A data frame giving, for each population parameter, the corresponding :

  • initialValue : (double) initial value
  • method : (string) estimation method
  • priorValue : (double) [MAP] typical value
  • priorSD : (double) [MAP] standard deviation

See Also

setPopulationParameterInformation

Click here to see examples

info = getPopulationParameterInformation()

info

name initialValue method typicalValue stdDeviation

ka_pop 1.0 MLE NA NA

V_pop 10.0 MAP 10.0 0.5

omega_ka 1.0 FIXED NA NA

## End(Not run)


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[Monolix] Initialize population parameters with the last estimated ones

Description

Set the initial value of all the population parameters present within the current project to the ones previously estimated.
These the values will be used in the population parameter estimation algorithm during the next scenario run.
WARNING: If there is any set after a run, it will not be possible to set the initial values as the structure of the project has changed since last results.

Usage

setInitialEstimatesToLastEstimates(fixedEffectsOnly = FALSE)

Arguments

fixedEffectsOnly (bool) If this boolean is set to TRUE, only the fixed effects are initialized to their last estimated values. Otherwise, individual variances and error model parameters are re-initialized too. Equals FALSE by default.

See Also

getEstimatedPopulationParameters getPopulationParameterInformation

Click here to see examples

setInitialEstimatesToLastEstimates() # fixedEffectsOnly = FALSE by default

setInitialEstimatesToLastEstimates(TRUE)

## End(Not run)


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[Monolix] Population parameters initialization and estimation method

Description

Set the initial value, the estimation method and, if relevant, the MAP parameters of one or several of the population parameters present within the current project (fixed effects + individual variances + error model parameters).
Available methods are:

  • "FIXED": Fixed
  • "MLE": Maximum Likelihood Estimation
  • "MAP": Maximum A Posteriori

Call getPopulationParameterInformation to get a list of the initializable population parameters present within the current project.

Usage

setPopulationParameterInformation(...)

Arguments

... A list of comma-separated pairs {paramName = list( initialValue = (double), method = (string)"method"}.
In case of "MAP" method, the user can specify the associated typical value and standard deviation values by using an additional list elements {paramName = list( priorValue = (double)1, priorSD = (double)2 )}.
By default, the prior value corresponds to the the population parameter and the prior standard deviation is set to 1.

See Also

getPopulationParameterInformation

Click here to see examples

setPopulationParameterInformation(Cl_pop = list(initialValue = 0.5, method = “FIXED”),

V_pop = list(initialValue = 1),

ka_pop = list(method = “MAP”, priorValue = 1, priorSD = 0.1))

## End(Not run)


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