Perform visual predictive check for NLME models
vpcmodel.Rd
Perform visual predictive check for NLME models
Arguments
- model
PK/PD model class object.
- vpcParams
VPC argument setup. See
NlmeVpcParams
. Ifmissing
, default values generated by NlmeVpcParams() are used.- params
Engine argument setup. See
engineParams
. The following arguments are the subject of interest: sort, ODE, rtolODE, atolODE, maxStepsODE. Ifmissing
, default values generated by engineParams(model) are used.- hostPlatform
Host definition for model execution. See
hostParams
. Ifmissing
, simple local host is used.- runInBackground
Set to
TRUE
to run in background and return prompt.- ...
Additional class initializer arguments for
NlmeVpcParams
orhostParams
, or arguments available insideengineParams
functions. IfengineParams
arguments are supplied through bothparams
argument and additional argument (i.e., ellipsis), then the arguments inparams
will be ignored and only the additional arguments will be used with warning. IfhostParams
arguments are supplied through bothhostPlatform
argument and additional argument, then its values will be overridden by additional arguments. In addition, ifNlmeVpcParams
arguments are supplied through bothvpcParams
argument and additional argument, then its slots will be overridden by additional arguments.
Value
if runInBackground is TRUE
, it returns job properties.
Otherwise,
If the function is called in an interactive mode, the resulting simulated tables and summary statistics tables will be loaded and presented as a list;
If the function is called in a non-interactive mode, it returns the full paths of the tables generated
Examples
if (FALSE) { # \dontrun{
job <- fitmodel(model)
# View estimation results
print(job)
finalModelVPC <- copyModel(model, acceptAllEffects = TRUE, modelName = "model_VPC")
# View the model
print(finalModelVPC)
# Set up VPC arguments to have PRED outputted to simulation output dataset "predout.csv"
vpcSetup <- NlmeVpcParams(outputPRED = TRUE)
# Run VPC using the default host, default values for the relevant NLME engine arguments
finalVPCJob <- vpcmodel(model = finalModelVPC, vpcParams = vpcSetup)
# the same as:
finalVPCJob <- vpcmodel(model = finalModelVPC, outputPRED = TRUE)
# Observed dataset predcheck0.csv
dt_ObsData <- finalVPCJob$predcheck0
# Simulation output dataset predout.csv
dt_SimData <- finalVPCJob$predout
# Add PRED from REPLICATE = 0 of simulation output dataset to observed input dataset
dt_ObsData$PRED <- dt_SimData[REPLICATE == 0]$PRED
# tidyvpc package VPC example:
library(magrittr)
library(tidyvpc)
# Create a regular VPC plot with binning method set to be "jenks"
binned_VPC <- observed(dt_ObsData, x = IVAR, yobs = DV) %>%
simulated(dt_SimData, ysim = DV) %>%
binning(bin = "jenks") %>%
vpcstats()
plot_binned_VPC <- plot(binned_VPC)
# Create a pcVPC plot with binning method set to be "jenks"
binned_pcVPC <- observed(dt_ObsData, x = IVAR, yobs = DV) %>%
simulated(dt_SimData, ysim = DV) %>%
binning(bin = "jenks") %>%
predcorrect(pred = PRED) %>%
vpcstats()
plot_binned_pcVPC <- plot(binned_pcVPC)
} # }