Description Usage Arguments Aesthetics Computed variables Examples
geom_qq
and stat_qq
produce quantilequantile plots. geom_qq_line
and
stat_qq_line
compute the slope and intercept of the line connecting the
points at specified quartiles of the theoretical and sample distributions.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17  geom_qq_line(mapping = NULL, data = NULL, geom = "path",
position = "identity", ..., distribution = stats::qnorm,
dparams = list(), line.p = c(0.25, 0.75), fullrange = FALSE,
na.rm = FALSE, show.legend = NA, inherit.aes = TRUE)
stat_qq_line(mapping = NULL, data = NULL, geom = "path",
position = "identity", ..., distribution = stats::qnorm,
dparams = list(), line.p = c(0.25, 0.75), fullrange = FALSE,
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)
stat_qq(mapping = NULL, data = NULL, geom = "point",
position = "identity", ..., distribution = stats::qnorm,
dparams = list(), na.rm = FALSE, show.legend = NA, inherit.aes = TRUE)

mapping 
Set of aesthetic mappings created by 
data 
The data to be displayed in this layer. There are three options: If A A 
geom 
The geometric object to use display the data 
position 
Position adjustment, either as a string, or the result of a call to a position adjustment function. 
... 
other arguments passed on to 
distribution 
Distribution function to use, if x not specified 
dparams 
Additional parameters passed on to 
line.p 
Vector of quantiles to use when fitting the QQ line, defaults
defaults to 
fullrange 
Should the qq line span the full range of the plot, or just the data 
na.rm 
If 
show.legend 
logical. Should this layer be included in the legends?

inherit.aes 
If 
stat_qq
understands the following aesthetics (required aesthetics are in bold):
sample
group
x
y
Learn more about setting these aesthetics in vignette("ggplot2specs")
stat_qq_line
understands the following aesthetics (required aesthetics are in bold):
sample
group
x
y
Learn more about setting these aesthetics in vignette("ggplot2specs")
Variables computed by stat_qq
:
sample quantiles
theoretical quantiles
Variables computed by stat_qq_line
:
xcoordinates of the endpoints of the line segment connecting the points at the chosen quantiles of the theoretical and the sample distributions
ycoordinates of the endpoints
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17  df < data.frame(y = rt(200, df = 5))
p < ggplot(df, aes(sample = y))
p + stat_qq() + stat_qq_line()
# Use fitdistr from MASS to estimate distribution params
params < as.list(MASS::fitdistr(df$y, "t")$estimate)
ggplot(df, aes(sample = y)) +
stat_qq(distribution = qt, dparams = params["df"]) +
stat_qq_line(distribution = qt, dparams = params["df"])
# Using to explore the distribution of a variable
ggplot(mtcars, aes(sample = mpg)) +
stat_qq() +
stat_qq_line()
ggplot(mtcars, aes(sample = mpg, colour = factor(cyl))) +
stat_qq() +
stat_qq_line()

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