VPC based on ui model
vpc_ui(
fit,
data = NULL,
n = 100,
bins = "jenks",
n_bins = "auto",
bin_mid = "mean",
show = NULL,
stratify = NULL,
pred_corr = FALSE,
pred_corr_lower_bnd = 0,
pi = c(0.05, 0.95),
ci = c(0.05, 0.95),
uloq = NULL,
lloq = NULL,
log_y = FALSE,
log_y_min = 0.001,
xlab = NULL,
ylab = NULL,
title = NULL,
smooth = TRUE,
vpc_theme = NULL,
facet = "wrap",
labeller = NULL,
vpcdb = FALSE,
verbose = FALSE,
...
)
# S3 method for nlmixrFitData
vpc(sim, ...)
# S3 method for nlmixrVpc
vpc(sim, ...)
# S3 method for ui
vpc(sim, ...)
fit  nlmixr fit object 

data  this is the data to use to augment the VPC fit. By
default is the fitted data, (can be retrieved by

n  Number of VPC simulations. By default 100 
bins  either "density", "time", or "data", "none", or one of the approaches available in classInterval() such as "jenks" (default) or "pretty", or a numeric vector specifying the bin separators. 
n_bins  when using the "auto" binning method, what number of bins to aim for 
bin_mid  either "mean" for the mean of all timepoints (default) or "middle" to use the average of the bin boundaries. 
show  what to show in VPC (obs_dv, obs_ci, pi, pi_as_area, pi_ci, obs_median, sim_median, sim_median_ci) 
stratify  character vector of stratification variables. Only 1 or 2 stratification variables can be supplied. 
pred_corr  perform predictioncorrection? 
pred_corr_lower_bnd  lower bound for the predictioncorrection 
pi  simulated prediction interval to plot. Default is c(0.05, 0.95), 
ci  confidence interval to plot. Default is (0.05, 0.95) 
uloq  Number or NULL indicating upper limit of quantification. Default is NULL. 
lloq  Number or NULL indicating lower limit of quantification. Default is NULL. 
log_y  Boolean indicting whether yaxis should be shown as logarithmic. Default is FALSE. 
log_y_min  minimal value when using log_y argument. Default is 1e3. 
xlab  label for x axis 
ylab  label for y axis 
title  title 
smooth  "smooth" the VPC (connect bin midpoints) or show bins as rectangular boxes. Default is TRUE. 
vpc_theme  theme to be used in VPC. Expects list of class vpc_theme created with function vpc_theme() 
facet  either "wrap", "columns", or "rows" 
labeller  ggplot2 labeller function to be passed to underlying ggplot object 
vpcdb  Boolean whether to return the underlying vpcdb rather than the plot 
verbose  show debugging information (TRUE or FALSE) 
...  Args sent to 
sim  this is usually a data.frame with observed data, containing the independent and dependent variable, a column indicating the individual, and possibly covariates. E.g. load in from NONMEM using read_table_nm. However it can also be an object like a nlmixr or xpose object 
Simulated dataset (invisibly)
Matthew L. Fidler