Calculation for quantile-quantile plot.

Usage

stat_qq(mapping = NULL, data = NULL, geom = "point", position = "identity", distribution = stats::qnorm, dparams = list(), na.rm = FALSE, show.legend = NA, inherit.aes = TRUE, ...)
geom_qq(mapping = NULL, data = NULL, geom = "point", position = "identity", distribution = stats::qnorm, dparams = list(), na.rm = FALSE, show.legend = NA, inherit.aes = TRUE, ...)

Arguments

mapping
The aesthetic mapping, usually constructed with aes or aes_string. Only needs to be set at the layer level if you are overriding the plot defaults.
data
A layer specific dataset - only needed if you want to override the plot defaults.
geom
The geometric object to use display the data
position
The position adjustment to use for overlapping points on this layer
distribution
Distribution function to use, if x not specified
dparams
Additional parameters passed on to distribution function.
na.rm
If FALSE (the default), removes missing values with a warning. If TRUE silently removes missing values.
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. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behaviour from the default plot specification, e.g. borders.
...
other arguments passed on to layer. This can include aesthetics whose values you want to set, not map. See layer for more details.

Description

Calculation for quantile-quantile plot.

Aesthetics

stat_qq understands the following aesthetics (required aesthetics are in bold):

  • sample
  • x
  • y

Computed variables

sample
sample quantiles

theoretical
theoretical quantiles

Examples

df <- data.frame(y = rt(200, df = 5)) p <- ggplot(df, aes(sample = y)) p + stat_qq()

p + geom_point(stat = "qq")

# Use fitdistr from MASS to estimate distribution params params <- as.list(MASS::fitdistr(df$y, "t")$estimate)
Warning message: NaNs produced Warning message: NaNs produced
ggplot(df, aes(sample = y)) + stat_qq(distribution = qt, dparams = params["df"])

# Using to explore the distribution of a variable ggplot(mtcars) + stat_qq(aes(sample = mpg))

ggplot(mtcars) + stat_qq(aes(sample = mpg, colour = factor(cyl)))