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, ...)

Arguments

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 getData), but it can be changed by specifying this argument.
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 prediction-correction?
pred_corr_lower_bnd: lower bound for the prediction-correction
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 y-axis should be shown as logarithmic. Default is FALSE.
log_y_min: minimal value when using log_y argument. Default is 1e-3.
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 rxSolve
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

Value

Simulated dataset (invisibly)

Author

Matthew L. Fidler