1. Raue, Bioinformatics 31(21), 2015↩︎

  2. Kaschek, dMod, 2016 (https://cran.r-project.org/package=dMod)↩︎

Runs an IQRnlmeProject

With "running" is meant that it will run the parameter estimation in the tool of choice (format of the IQRnlmeProject). If run then also post-processing is done to obtain standard diagnostics and a parameter table. If project has already been run then nothing is done.

run_IQRnlmeProject(
  projectPath,
  ncores = 1,
  Nparallel = 1,
  FLAGrerun = FALSE,
  FLAGclean = TRUE,
  FLAGgof = TRUE,
  FLAGgofStratify = FALSE,
  FLAGremoveRESULTSORIG = FALSE
)

Arguments

projectPath

An IQRnlmeProject or a character string with the path to an IQRnlmeProject folder.

ncores

Number of cores if use of parallelization of a single model run (NONMEM and MONOLIX. Not yet for NLMIXR)

Nparallel

Number of models to run in parallel (only used when project is a IQRnlmeProjectMulti.

FLAGrerun

TRUE: Models will be rerun even if results already present. FALSE: Models for which results are present will not be rerun. This only impacts the "running" of the models. GoF plots will still be generated. This allows for separation of running and GoF plot generation.

FLAGclean

TRUE: will remove unnecessary (NONMEM/NLMIXR) files

FLAGgof

TRUE: Create GoF plots for all runs FALSE: Do not create GoF plots. NOTE THAT GoF plots are out of scope of WP3.

FLAGgofStratify

TRUE: additional GoF plots stratified by covariates in the dataset are produced. For continuous covariates 2 groups are selected (smaller than median and greater equal median). FALSE: no stratification is done (faster).

FLAGremoveRESULTSORIG

Logical. If TRUE then the RESULTSORIG folder will be removed. this will save a considerable amount of space on disk.

Value

An IQRnlmeProject is returned.

See also

Other IQRnlmeProject: IQRnlmeEst(), IQRnlmeProject(), addCovariateToModelSpec_IQRest(), addPar_modelSpec(), as_IQRnlmeProjectMulti(), as_IQRnlmeProject(), bootstrap_IQRnlmeProject(), compareModels_IQRnlmeProjectMulti(), convertETAINDIVPRED_IQRnlmeProject(), covariateEffect_IQRnlmeProject(), createDataVPC_IQRnlmeProject(), data_IQRest(), dosing_IQRest(), duplicate_IQRnlmeProject(), eigenvalues_IQRnlmeProject(), exportVirtualSubjects_IQRnlmeProject(), getData_IQRnlmeProject(), getETAs_IQRnlmeProject(), getEst_IQRnlmeProject(), getHeader_IQRnlmeProject(), getIndivParameters_IQRnlmeProject(), getIndivPredictions_IQRnlmeProject(), getModel_IQRnlmeProject(), getObsPred_IQRnlmeProject(), getPopParameters_IQRnlmeProject(), getResults_IQRnlmeProjectMulti(), getResults_IQRnlmeProject(), hasrun_IQRnlmeProjectMulti(), hasrun_IQRnlmeProject(), informationContent_IQRnlmeProject(), is_IQRnlmeEst(), is_IQRnlmeProjectMulti(), is_IQRnlmeProject(), is_MONOLIX_IQRnlmeProject(), is_NLMIXR_IQRnlmeProject(), is_NONMEM_IQRnlmeProject(), modelSpec_IQRest(), outlier_IQRnlmeProject(), plot.IQRnlmeProjectMulti(), plot.IQRnlmeProject(), plotConvergence_IQRnlmeProject(), plotETACOV_IQRnlmeProject(), plotETA_IQRnlmeProject(), plotGOF_IQRnlmeProject(), plotINDIVSIM_IQRnlmeProject(), plotINDIV_IQRnlmeProject(), plotVPC_IQRdataVPC(), pred_IQRnlmeProject(), print.IQRnlmeEst(), print.IQRnlmeProjectMulti(), print.IQRnlmeProject(), print_modelSpec(), run_IQRnlmeProjectMulti(), sample_IQRnlmeProject(), scm_IQRnlmeProject(), summary.IQRnlmeProjectMulti(), summary.IQRnlmeProject(), summaryComments_IQRnlmeProjectMulti(), summaryCorrelations_IQRnlmeProjectMulti(), summaryCovariates_IQRnlmeProjectMulti(), summaryParameters_IQRnlmeProjectMulti(), vpc_IQRnlmeProject()