Create GOF plots for IQRnlmeProjects
plotGOF_IQRnlmeProject.Rd
Works for all interfaced NLME tools (NONMEM, MONOLIX, NLMIXR). If called without a filename it will return the ggplot objects as a list. If called with filename it will generate the PDF file at the given location. The data used for the plot are returned as attr(,"plotData") in each list element.
plotGOF_IQRnlmeProject(
projectPath,
outputNr = 1,
stratCov = NULL,
filename = NULL,
plotLog = TRUE,
FLAGuseBLQinCalc = FALSE,
DVPRED.MINMAXXY = NULL,
RES.MINMAXY = NULL
)
Arguments
- projectPath
Path to the NLME project folder
- outputNr
Number of the output of the model to plot the GOF plots for
- stratCov
Character string with name of covariate to use for stratification
- filename
Name of file to export plots to (PDF)
- plotLog
Plotting on linear axes is always done. If this is set to TRUE then in addition plots on log axes might be produced if the data allows (>0)
- FLAGuseBLQinCalc
Flag whether BLQ values should be used for calculation of smoothing splines (Default: FALSE)
- DVPRED.MINMAXXY
Vector with 2 elements to be used as min and max values for the X and Y axes in DV/PRED and DV/IPRED plots. If NULL then default settings are used, plotting all data
- RES.MINMAXY
Vector with 2 elements to be used as min and max values for the Y axis in residuals vs TIME, TAD and PRED and the X axis in the histogram plots of the residuals. If NULL then default settings are used, plotting all data.
Value
List with ggplot2 objects (one per page). Including "plotData" attribute, containing the data that were plotted
See also
Other IQRnlmeProject:
IQRnlmeEst()
,
IQRnlmeProject()
,
addCovariateToModelSpec_IQRest()
,
addPar_modelSpec()
,
as_IQRnlmeProject()
,
as_IQRnlmeProjectMulti()
,
bootstrap_IQRnlmeProject()
,
compareModels_IQRnlmeProjectMulti()
,
convertETAINDIVPRED_IQRnlmeProject()
,
covariateEffect_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_IQRnlmeProject()
,
getResults_IQRnlmeProjectMulti()
,
hasrun_IQRnlmeProject()
,
hasrun_IQRnlmeProjectMulti()
,
informationContent_IQRnlmeProject()
,
is_IQRnlmeEst()
,
is_IQRnlmeProject()
,
is_IQRnlmeProjectMulti()
,
is_MONOLIX_IQRnlmeProject()
,
is_NLMIXR_IQRnlmeProject()
,
is_NONMEM_IQRnlmeProject()
,
modelSpec_IQRest()
,
outlier_IQRnlmeProject()
,
plot.IQRnlmeProject()
,
plot.IQRnlmeProjectMulti()
,
plotBLQVPC_IQRdataVPC()
,
plotConvergence_IQRnlmeProject()
,
plotETACOV_IQRnlmeProject()
,
plotETA_IQRnlmeProject()
,
plotINDIVSIM_IQRnlmeProject()
,
plotINDIV_IQRnlmeProject()
,
plotMEANSIM_IQRnlmeProject()
,
plotVPC_IQRdataVPC()
,
pred_IQRnlmeProject()
,
print.IQRnlmeEst()
,
print.IQRnlmeProject()
,
print.IQRnlmeProjectMulti()
,
print_modelSpec()
,
run_IQRnlmeProject()
,
run_IQRnlmeProjectMulti()
,
sample_IQRnlmeProject()
,
scm_IQRnlmeProject()
,
summary.IQRnlmeProject()
,
summary.IQRnlmeProjectMulti()
,
summaryComments_IQRnlmeProjectMulti()
,
summaryCorrelations_IQRnlmeProjectMulti()
,
summaryCovariates_IQRnlmeProjectMulti()
,
summaryParameters_IQRnlmeProjectMulti()
,
vpc_IQRnlmeProject()