Description of the functions of the API
getCorrelationOfEstimates  Get the inverse of the last estimated Fisher matrix computed either by all the Fisher methods used during the last scenario run or by the specific one passed in argument. 
getEstimatedIndividualParameters  Get the last estimated values for each subject of some of the individual parameters present within the current project. 
getEstimatedLogLikelihood  Get the values computed by using a loglikelihood algorithm during the last scenario run, with or without a methodbased filter. 
getEstimatedPopulationParameters  Get the last estimated value of some of the population parameters present within the current project (fixed effects + individual variances + correlations + latent probabilities + error model parameters). 
getEstimatedRandomEffects  Get the random effects for each subject of some of the individual parameters present within the current project. 
getEstimatedStandardErrors  Get the last estimated standard errors of population parameters computed either by all the Fisher methods used during the last scenario run or by the specific one passed in argument. 
getLaunchedTasks  Get a list of the tasks which have results to provide. 
getSAEMiterations  Retrieve the successive values of some of the population parameters present within the current project (fixed effects + individual variances + correlations + latent probabilities + error model parameters) during the previous run of the SAEM algorithm. 
getSimulatedIndividualParameters  Get the simulated values for each replicate of each subject of some of the individual parameters present within the current project. 
getSimulatedRandomEffects  Get the simulated values for each replicate of each subject of some of the individual random effects present within the current project. 
getTests  Get the results of performed statistical tests. 
[Monolix] Get the inverse of the Fisher Matrix
Description
Get the inverse of the last estimated Fisher matrix computed either by all the Fisher methods used during the last scenario run or by the specific one passed in argument.
WARNING: The Fisher matrix cannot be accessible until the Fisher algorithm has been launched once.
The user can choose to display only the Fisher matrix estimated with a specific method.
Existing Fisher methods :
Fisher by Linearization  “linearization” 
Fisher by Stochastic Approximation  “stochasticApproximation” 
WARNING: Only the methods which have been used during the last scenario run can provide results.
Usage
getCorrelationOfEstimates(method = "")
Arguments
method 
[optional](string) Fisher method whose results should be displayed. If this field is not specified, the results provided by all the methods used during the last scenario run are displayed. 
Value
A list whose each field contains the Fisher matrix computed by one of the available Fisher methods used during the ast scenario run.
A matrix is defined as a structure containing the following fields :
rownames  list of row names 
columnnames  list of column names 
rownumber  number of rows 
data  vector<…> containing matrix raw values (column major) 
Click here to see examples
getCorrelationOfEstimates(“linearization”)
> list( linearization = list(data = c(1,0,0,0,1,0.06,0,0.06,1),
rownumber = 3,
rownames = c(“Cl_pop”,”omega_Cl”,”a”),
columnnames = c(“Cl_pop”,”omega_Cl”,”a”)))
getCorrelationOfEstimates()
> list(linearization = list(…), stochasticApproximation = list(…) )
## End(Not run)
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[Monolix] Get last estimated individual parameter values
Description
Get the last estimated values for each subject of some of the individual parameters present within the current project.
WARNING: Estimated individual parameters values cannot be accessible until the individual estimation algorithm has been launched once.
NOTE: The user can choose to display only the individual parameter values estimated with a specific method.
Existing individual estimation methods :
Conditional Mean SAEM  “saem” 
Conditional Mean  “conditionalMean” 
Conditional Mode  “conditionalMode” 
WARNING: Only the methods which have been used during the last scenario run can provide estimation results.
Usage
getEstimatedIndividualParameters(..., method = "")
Arguments
... 
(string) Name of the individual parameters whose values must be displayed. Call getIndividualParameterModel to get a list of the individual parameters present within the current project.

method 
[optional](string) Individual parameter estimation method whose results should be displayed. If there are latent covariate used in the model, the estimated modality is displayed too If this field is not specified, the results provided by all the methods used during the last scenario run are displayed. 
Value
A data frame giving, for each wanted method, the last estimated values of the individual parameters of interest for each subject with the corresponding standard deviation values.
See Also
Click here to see examples
indivParams = getEstimatedIndividualParameters()
# retrieve the values of all the available individual parameters for all methods
> $saem
id Cl V ka
1 0.28 7.71 0.29
. … … …
N 0.1047.62 1.51
indivParams = getEstimatedIndividualParameters(“Cl”, “V”, method = “conditionalMean”)
# retrieve the values of the individual parameters “Cl” and “V”
# estimated by the conditional mode method
## End(Not run)
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[Monolix] Get LogLikelihood values
Description
Get the values computed by using a loglikelihood algorithm during the last scenario run, with or without a methodbased filter.
WARNING: The loglikelihood values cannot be accessible until the loglikelihood algorithm has been launched once.
The user can choose to display only the loglikelihood values computed with a specific method.
Existing loglikelihood methods :
Loglikelihood by Linearization  “linearization” 
Loglikelihood by Important Sampling  “importanceSampling” 
WARNING: Only the methods which have been used during the last scenario run can provide results.
Usage
getEstimatedLogLikelihood(method = "")
Arguments
method 
[optional](string) Loglikelihood method whose results should be displayed. If this field is not specified, the results provided by all the methods used during the last scenario run are retrieved. 
Value
A list associating the name of each method passed in argument to the corresponding loglikelihood values computed by during the last scenario run.
Click here to see examples
getEstimatedLogLikelihood()
> list( linearization = [LL = 170.505, AIC = 350.280, BIC = 365.335] ,
importanceSampling = […] )
getEstimatedLogLikelihood(“linearization”)
> list( linearization = [LL = 170.505, AIC = 350.280, BIC = 365.335] )
## End(Not run)
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[Monolix] Get last estimated population parameter value
Description
Get the last estimated value of some of the population parameters present within the current project (fixed effects + individual variances + correlations + latent probabilities + error model parameters).
WARNING: Estimated population parameters values cannot be accessible until the SAEM algorithm has been launched once.
Usage
getEstimatedPopulationParameters(...)
Arguments
... 
[optional] (array<string>) Names of the population parameters whose value must be displayed. Call getPopulationParameterInformation to get a list of the population parameters present within the current project.If this field is not specified, the function will retrieve the values of all the available population parameters. 
Value
A named vector containing the last estimated value of each one of the population parameters passed in argument.
Click here to see examples
getEstimatedPopulationParameters(“V_pop”) > [V_pop = 0.5]
getEstimatedPopulationParameters(“V_pop”,”Cl_pop”) > [V_pop = 0.5, Cl_pop = 0.25]
getEstimatedPopulationParameters() > [V_pop = 0.5, Cl_pop = 0.25, ka_pop = 0.05]
## End(Not run)
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[Monolix] Get estimated the random effects
Description
Get the random effects for each subject of some of the individual parameters present within the current project.
WARNING: Estimated random effects cannot be accessible until the individual estimation algorithm has been launched once.
The user can choose to display only the random effects estimated with a specific method.
NOTE: The random effects are defined in the gaussian referential, e.g. if ka is lognormally distributed around ka_pop, eta_i = log(ka_i)log(ka_pop)
Existing individual estimation methods :
Conditional Mean SAEM  “saem” 
Conditional Mean  “conditionalMean” 
Conditional Mode  “conditionalMode” 
WARNING: Only the methods which have been used during the last scenario run can provide estimation results. Please call getLaunchedTasks
to get a list of the methods whose results are available.
Usage
getEstimatedRandomEffects(..., method = "")
Arguments
... 
(string) Name of the individual parameters whose random effects must be displayed. Call getIndividualParameterModel to get a list of the individual parameters present within the current project.

method 
[optional](string) Individual parameter estimation method whose results should be displayed. If this field is not specified, the results provided by all the methods used during the last scenario run are displayed. 
Value
A data frame giving, for each wanted method, the last estimated eta values of the individual parameters of interest for each subject with the corresponding standard deviation values.
See Also
getEstimatedIndividualParameters
Click here to see examples
etaParams = getEstimatedRandomEffects()
# retrieve the values of all the available random effects for all methods
# without the associated standard deviations
> $saem
id Cl V ka
1 0.28 7.71 0.29
. … … …
N 0.1047.62 1.51
etaParams = getEstimatedRandomEffects(“Cl”, “V”, method = “conditionalMode”)
# retrieve the values of the individual parameters “Cl” and “V”
# estimated by the conditional mean from SAEM algorithm
## End(Not run)
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[Monolix] Get standard errors of population parameters
Description
Get the last estimated standard errors of population parameters computed either by all the Fisher methods used during the last scenario run or by the specific one passed in argument.
WARNING: The standard errors cannot be accessible until the Fisher algorithm has been launched once.
Existing Fisher methods :
Fisher by Linearization  “linearization” 
Fisher by Stochastic Approximation  “stochasticApproximation” 
WARNING: Only the methods which have been used during the last scenario run can provide results.
Usage
getEstimatedStandardErrors(method = "")
Arguments
method 
[optional](string) Fisher method whose results should be displayed. If this field is not specified, the results provided by all the methods used during the last scenario run are retrieved 
Value
A list associating each retrieved Fisher algorithm method to a data frame containing the standard errors and relative standard errors (
Click here to see examples
getEstimatedStandardErrors() >
$linearization
parameter se rse
ka_pop 0.313449586 20.451556
V_pop 0.020422507 4.483500
omega_V 0.037975960 30.072470
omega_Cl 0.062976601 23.270939
$stochasticApproximation
parameter se rse
ka_pop 0.311284296 20.310278
V_pop 0.020424882 4.484022
omega_V 0.161053665 24.000077
omega_Cl 0.035113095 27.805419
## End(Not run)
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[Monolix] Get tasks with results
Description
Get a list of the tasks which have results to provide. A task is the association of:
 an algorithm (string)
 a vector of methods (string) relative to this algorithm for the standardErrorEstimation and the loglikelihoodEstimation, TRUE or FALSE for the other one.
Usage
getLaunchedTasks()
Value
The list of tasks with results, indexed by algorithm names.
Click here to see examples
tasks = getLaunchedTasks()
tasks
> $populationParameterEstimation = TRUE
$conditionalModeEstimation = TRUE
$standardErrorEstimation = “linearization”
## End(Not run)
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[Monolix] Get SAEM algorithm iterations
Description
Retrieve the successive values of some of the population parameters present within the current project (fixed effects + individual variances + correlations + latent probabilities + error model parameters) during the previous run of the SAEM algorithm.
WARNING: Convergence history of population parameters values cannot be accessible until the SAEM algorithm has been launched once.
Usage
getSAEMiterations(...)
Arguments
... 
[optional] (array<string>) Names of the population parameters whose convergence history must be displayed. Call getPopulationParameterInformation to get a list of the population parameters present within the current project.If this field is not specified, the function will retrieve the values of all the available population parameters. 
Value
A list containing a pair composed by the number of exploratory and smoothing iterations and a data frame which associates each wanted population parameter to its successive values over SAEM algorithm iterations.
Click here to see examples
report = getSAEMiterations()
report
> $iterationNumbers
c(50,25)
$estimates
V Cl
0.25 0
0.3 0.5
. .
0.35 0.25
## End(Not run)
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[Monolix] Get simulated individual parameters
Description
Get the simulated values for each replicate of each subject of some of the individual parameters present within the current project.
WARNING: Simulated individual parameters values cannot be accessible until the individual estimation with conditional mean algorithm has been launched once.
Usage
getSimulatedIndividualParameters(...)
Arguments
... 
(string) Name of the individual parameters whose values must be displayed. Call getIndividualParameterModel to get a list of the individual parameters present within the current project.

Value
A list giving the last simulated values of the individual parameters of interest for each replicate of each subject.
See Also
Click here to see examples
simParams = getSimulatedIndividualParameters()
# retrieve the values of all the available individual parameters
simParams
rep id Cl V ka
1 1 0.022 0.37 1.79
1 2 0.033 0.42 0.92
. . … … …
2 1 0.021 0.33 1.47
. . … … …
## End(Not run)
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[Monolix] Get simulated random effects
Description
Get the simulated values for each replicate of each subject of some of the individual random effects present within the current project.
WARNING: Simulated individual random effects values cannot be accessible until the individual estimation algorithm with conditional mean has been launched once.
Usage
getSimulatedRandomEffects(...)
Arguments
... 
(string) Name of the individual parameters whose values must be displayed. Call getIndividualParameterModel to get a list of the individual parameters present within the current project.

Value
A list giving the last simulated values of the individual random effects of interest for each replicate of each subject.
See Also
getIndividualParameterModel
Click here to see examples
simEtas = getSimulatedRandomEffects()
# retrieve the values of all the available individual random effects
simEtas
rep id Cl V ka
1 1 0.022 0.37 1.79
1 2 0.033 0.42 0.92
. . … … …
2 1 0.021 0.33 1.47
. . … … …
## End(Not run)
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[Monolix] Get statistical tests results
Description
Get the results of performed statistical tests.
Existing tests: Wald, Individual parameters normality, individual parameters marginal distribution, random effects normality,
random effects correlation, individual parameters vs covariates correlation, random effects vs covariates correlation,
residual normality and residual symmetry.
WARNING: Only the tests performed during the last scenario run can provide results.
Usage
getTests()
Value
A list associating the name of the test to the corresponding results values computed during the last scenario run.
Click here to see examples
getTests()
> list( wald = […] ,
individualParametersNormality = […] ,
… )
## End(Not run)
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