Stepwise Parameter Modeling for QSP - fixed effects

spm_IQRsysProject.Rd

Supports identification of fixed effects to consider in the estimation. The algorithm is based on identifiability of a parameter, given the available data. Parameters of interest are defined and included one by one. Estimation is performed and parameters to be kept in the next iteration are selected by the smallest RSE. If RSE for a parameter in an iteration is > RSEmaxRemove then it is not considered further in the next iteration. If all remaining parameters have RSE>RSEmax then the algorithm stops. No IIV in this approach! Currently limited to positive parameters only.

spm_IQRsysProject(
  path,
  model,
  dosing,
  data,
  SPM_POPvalues0,
  POPvalues0 = NULL,
  errorModel = NULL,
  ncores = 1,
  Nparallel = 1,
  RSEmax = 50,
  RSEmaxRemove = 100,
  FLAGclean = TRUE,
  SIMOPT.nauxtimes = 0,
  SIMOPT.hmax = NULL,
  SIMOPT.atol = 1e-06,
  SIMOPT.rtol = 1e-06
)

Arguments

path

Path to where to store all the models in all the iterations

model

IQRmodel object to use

dosing

See dosing_IQRest

data

See data_IQRest

SPM_POPvalues0

Named vector with parameter names and values to test

POPvalues0

Named vector with parameter names and values to always have in the model

errorModel

See modelSpec_IQRsysEst

ncores

Number of cores for a single model run

Nparallel

Number of models to run in parallel

RSEmax

If all RSEs in an iteration above this value, the algorithm stops

RSEmaxRemove

If RSE for parameter above this value, the parameter is not considered further in the next iteration

FLAGclean

If TRUE then all models are removed, keeping only the table result files - saves a lot of diskspace!

SIMOPT.nauxtimes

Number of additional auxiliary times for integrator

SIMOPT.hmax

Maximum stepsize of the integrator. Passed to IQRsysProject. Set if experiencing numerical issues with TIME offsets in the dataset.

SIMOPT.atol

Absolute error tolerance for integrator

SIMOPT.rtol

Relative error tolerance for integrator

Value

Results are displayed in the console and a list is returned with a table and a vector with parameters and values identified. In addition in the path and in each iteration folder a table with information is exported.

See also

Other QSP: IQRsysEst(), IQRsysModel(), IQRsysProject(), addOutputs_IQRmodel(), addRelations_IQRmodel(), as_IQRsysEst(), as_IQRsysProjectMulti(), as_IQRsysProject(), comparePars_IQRsysModel(), duplicate_IQRsysProject(), exportVariant_IQRmodel(), exportVirtualSubjects_IQRnlmeProject(), export_IQRsysData(), getDosing_IQRsysModel(), getEmpiricalETACovarianceMatrix_IQRsysProject(), getOptTrace_IQRsysProject(), getPars_IQRoptTrace(), getPars_IQRsysModel(), getPrediction_IQRsysModel(), hasrun_IQRsysProject(), importVariant_IQRmodel(), import_IQRsysData(), is_IQRsysEst(), is_IQRsysModel(), is_IQRsysProjectMulti(), is_IQRsysProject(), load_IQRsysProject(), modelSpec_IQRsysEst(), model_IQRsysModel(), offsetTIME_IQRsysData(), plotDVPRED_IQRsysModel(), plotFit_IQRsysModel(), plotPars_IQRsysModel(), plotPred_IQRsysModel(), plotProfile_IQRsysModel(), plotWRES_IQRsysModel(), plotWaterfall_IQRsysModel(), plot_IQRoptTrace(), plot_IQRsysModel(), print.IQRsensitivity(), print.IQRsysProject(), profile_IQRsysModel(), replaceTerms_IQRmodel(), run_IQRsysProjectMulti(), run_IQRsysProject(), sample_IQRsysModel(), sensitivity_IQRmodel(), setPars_IQRsysModel(), sim_IQRsysModel(), sim_IQRvirtualSubjects(), simbio_CSV2namedVector(), simbio_updateParamIC_IQRmodel(), spmIIV_IQRsysProject(), switchOpt_IQRsysModel(), tablePars_IQRsysModel()