qqPoints: Quantile Comparison Data

In psre: Presenting Statistical Results Effectively

Quantile Comparison Data

Description

Makes data that can be used in quantile comparison plots.

Usage

qqPoints(
  x,
  distribution = "norm",
  line = c("quartiles", "robust", "none"),
  conf = 0.95,
  ...
)

Arguments

x	vector of values whose quantiles will be calculated.
distribution	String giving the theoretical distribution against which the quantiles of the observed data will be compared. These need to be functions that have q and d functions in R. Defaults to "norm".
line	String giving the nature of the line that should be drawn through the points. If "quartiles", the line is drawn connecting the 25th and 75th percentiles. If "robust" a robust linear model is used to fit the line.
conf	Confidence level to be used.
...	Other parameters to be passed down to the quantile function.

Value

A data frame with variables x observed quantiles, theo the theoretical quantiles and lwr and upr the confidence bounds. The slope and intercept of the line running through the points are returned as a and b as an attribute of the data.a

Examples

x <- rchisq(100, 3)
qqdf <- qqPoints(x)
a <- attr(qqdf, "ab")[1]
b <- attr(qqdf, "ab")[2]
l <- min(qqdf$theo) * b + a
u <- max(qqdf$theo) * b + a
library(ggplot2)
ggplot(qqdf, aes(x=theo, y=x)) +
  geom_ribbon(aes(ymin=lwr, ymax=upr), alpha=.15) +
  geom_segment(aes(x=min(qqdf$theo), xend=max(qqdf$theo), y = l, yend=u)) +
  geom_point(shape=1) +
  theme_classic() +
  labs(x="Theoretical Quantiles",
       y="Observed Quantiles")

psre documentation built on Aug. 8, 2022, 5:05 p.m.