Skip to content

geom_qq() and stat_qq() produce quantile-quantile 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.

Usage

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
)

Arguments

mapping

Set of aesthetic mappings created by aes(). If specified and inherit.aes = TRUE (the default), it is combined with the default mapping at the top level of the plot. You must supply mapping if there is no plot mapping.

data

The data to be displayed in this layer. There are three options:

If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot().

A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify() for which variables will be created.

A function will be called with a single argument, the plot data. The return value must be a data.frame, and will be used as the layer data. A function can be created from a formula (e.g. ~ head(.x, 10)).

geom

The geometric object to use to display the data for this layer. When using a stat_*() function to construct a layer, the geom argument can be used to override the default coupling between stats and geoms. The geom argument accepts the following:

  • A Geom ggproto subclass, for example GeomPoint.

  • A string naming the geom. To give the geom as a string, strip the function name of the geom_ prefix. For example, to use geom_point(), give the geom as "point".

  • For more information and other ways to specify the geom, see the layer geom documentation.

position

A position adjustment to use on the data for this layer. This can be used in various ways, including to prevent overplotting and improving the display. The position argument accepts the following:

  • The result of calling a position function, such as position_jitter(). This method allows for passing extra arguments to the position.

  • A string naming the position adjustment. To give the position as a string, strip the function name of the position_ prefix. For example, to use position_jitter(), give the position as "jitter".

  • For more information and other ways to specify the position, see the layer position documentation.

...

Other arguments passed on to layer()'s params argument. These arguments broadly fall into one of 4 categories below. Notably, further arguments to the position argument, or aesthetics that are required can not be passed through .... Unknown arguments that are not part of the 4 categories below are ignored.

  • Static aesthetics that are not mapped to a scale, but are at a fixed value and apply to the layer as a whole. For example, colour = "red" or linewidth = 3. The geom's documentation has an Aesthetics section that lists the available options. The 'required' aesthetics cannot be passed on to the params.

  • When constructing a layer using a stat_*() function, the ... argument can be used to pass on parameters to the geom part of the layer. An example of this is stat_density(geom = "area", outline.type = "both"). The geom's documentation lists which parameters it can accept.

  • Inversely, when constructing a layer using a geom_*() function, the ... argument can be used to pass on parameters to the stat part of the layer. An example of this is geom_area(stat = "density", adjust = 0.5). The stat's documentation lists which parameters it can accept.

  • The key_glyph argument of layer() may also be passed on through .... This can be one of the functions described as key glyphs, to change the display of the layer in the legend.

distribution

Distribution function to use, if x not specified

dparams

Additional parameters passed on to distribution function.

line.p

Vector of quantiles to use when fitting the Q-Q line, defaults defaults to c(.25, .75).

fullrange

Should the q-q line span the full range of the plot, or just the data

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. It can also be a named logical vector to finely select the aesthetics to display.

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().

Aesthetics

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

Learn more about setting these aesthetics in vignette("ggplot2-specs").

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

Learn more about setting these aesthetics in vignette("ggplot2-specs").

Computed variables

These are calculated by the 'stat' part of layers and can be accessed with delayed evaluation.
Variables computed by stat_qq():

  • after_stat(sample)
    Sample quantiles.

  • after_stat(theoretical)
    Theoretical quantiles.

Variables computed by stat_qq_line():

  • after_stat(x)
    x-coordinates of the endpoints of the line segment connecting the points at the chosen quantiles of the theoretical and the sample distributions.

  • after_stat(y)
    y-coordinates of the endpoints.

Examples

# \donttest{
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)
#> Warning: NaNs produced
#> Warning: NaNs produced
#> Warning: NaNs produced
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()

# }