nonmem2R (version 0.2.4)

stat_QQVPC: Add VPC confidence interval for Quantile-Quantile Plots

Description

Add Visual predictive check confidence interval for Quantile-Quantile Plots with ggplot2.

Usage

stat_QQVPC(mapping = NULL, data = NULL, geom = "ribbon",
  position = "identity", na.rm = FALSE, show.legend = NA,
  inherit.aes = TRUE, confidence.level = 0.95, ...)

Arguments

mapping

Set of aesthetic mappings created by aes or aes_.

data

The data to be displayed in this layer.

geom

Use to override the default geom

position

Position adjustment, either as a string, or the result of a call to a position adjustment function.

na.rm

If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.

show.legend

logical. Should this layer be included in the legends? NA, the default, includes if any aesthetics are mapped. FALSE never includes, and TRUE always includes.

inherit.aes

If FALSE, overrides the default aesthetics, rather than combining with them.

confidence.level

Confidence level for confidence intervals, default=0.95

...

other arguments passed on to layer.

Aesthetics

geom_smooth understands the following aesthetics (required aesthetics are in bold):
x, alpha, colour, fill, group, shape, size, stroke

Details

Provide Visual predictive check confidence interval for normal QQplot under the assumption of normal distribution. With confidence.level=0.95, by chance one 1 of 20 data points may fall outside the confidence interval when data truly are normal distributed. Confidence intervals are based on repeated simulation of normal distributed data with mean and sd equal to the mean and sd of input data and confidence limits are defined by the quantiles of simulated data.

Examples

dd<-data.frame(gr=c(rep("A",20),rep("B",40)))
dd$dv<-2*(dd$gr=="B")+rnorm(nrow(dd))/(1+2*(dd$gr=="A"))
dd<-dd[order(dd$gr,dd$dv),]
dd$px<-NA
for(gri in levels(dd$gr)){
  dd$px[dd$gr==gri]<-qqnorm(dd$dv[dd$gr==gri],plot=FALSE)$x
}
ggplot(dd, aes(dv)) +
  stat_QQVPC(alpha=0.25)+
  stat_QQnorm()+
  facet_wrap(~gr)
if (FALSE) {
ggplot(dd, aes(dv,color=factor(gr))) +
  stat_QQVPC(alpha=0.25) +
  stat_QQnorm()
}