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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