Stepwise Parameter Modeling for QSP - random effects
spmIIV_IQRsysProject.Rd
Supports identification of random effects to consider in the estimation. The algorithm is based on reduction of OBJ by inclusion of IIV on a parameter. In each iteration single IIV elements are considered and the IIV is retained that results in the lowest objective function value. Then the next iteration is done. Currently limited to positive parameters only ("L" IIV).
spmIIV_IQRsysProject( path, model, dosing, data, POPvalues0, SPM_IIVvalues0 = NULL, IIVvalues0 = NULL, errorModel = NULL, ncores = 1, Nparallel = 1, 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 |
POPvalues0 | Named vector with fixed effect parameters to use in the model |
SPM_IIVvalues0 | Named vector with random effect parameters to test in the model. If not provided the default is 50 percent CV for all parameters in POPvalues0 |
IIVvalues0 | Named vector with random effect parameters 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 |
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()
,
spm_IQRsysProject()
,
switchOpt_IQRsysModel()
,
tablePars_IQRsysModel()