getAssessmentResults
[Monolix] Get the results of the convergence assessment
Get the results of the convergence assessment. The populationParameters are always included and standardErrors and logLikelihood
are included when extendedEstimation is TRUE in the assessment settings.
Usage
getAssessmentResults()Value
A vector of lists containing, for each assessment run:
populationParameters: results of population parameter estimation using SAEM:nbexploratoryiterations(integer) number of iterations during exploratory phasenbsmoothingiterations(integer) number of iterations during smoothing phaseconvergence(data.frame) convergence history of estimated population parameters and convergence indicator (-2*log-likelihood)
standardErrors: [optional] results of standard errors estimation:method(character) fisher method used (stochasticApproximation or linearization)values(vector) standard error associated to each population parameter
loglikelihood: [optional] results of log-likelihood estimationmethod(character) fisher method used (importanceSampling or linearization)AIC(double) Akaike Information CriterionBIC(double) Bayesian Information CriterionBICc(double) modified BICLL(double) log likelihoodchosenDegree(integer) [importanceSampling]standardError(double) [importanceSampling]convergence(data.frame) [importanceSampling]
See also
runAssessment to run the assessment
Examples
if (FALSE) {
initializeLixoftConnectors("monolix")
project_file <- file.path(getDemoPath(), "1.creating_and_using_models", "1.1.libraries_of_models", "theophylline_project.mlxtran")
loadProject(project_file)
assesSettings <- getAssessmentSettings()
assesSettings$initialParameters$fixed <- rep(FALSE, 3)
assesSettings$initialParameters$min <- rep(0, 3)
assesSettings$initialParameters$max <- c(1.5, 1, 0.5)
assesSettings$extendedEstimation <- TRUE
runAssessment(settings = assesSettings)
res = getAssessmentResults()
}