Add quantile lines from a quantile regression.


geom_quantile(mapping = NULL, data = NULL, stat = "quantile", position = "identity", ..., lineend = "butt", linejoin = "round", linemitre = 1, na.rm = FALSE, show.legend = NA, inherit.aes = TRUE)
stat_quantile(mapping = NULL, data = NULL, geom = "quantile", position = "identity", ..., quantiles = c(0.25, 0.5, 0.75), formula = NULL, method = "rq", method.args = list(), na.rm = FALSE, show.legend = NA, inherit.aes = TRUE)


Set of aesthetic mappings created by aes or 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.
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.
Position adjustment, either as a string, or the result of a call to a position adjustment function.
other arguments passed on to layer. These are often aesthetics, used to set an aesthetic to a fixed value, like color = "red" or size = 3. They may also be parameters to the paired geom/stat.
Line end style (round, butt, square)
Line join style (round, mitre, bevel)
Line mitre limit (number greater than 1)
If FALSE (the default), removes missing values with a warning. If TRUE silently removes missing values.
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.
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.
geom, stat
Use to override the default connection between geom_quantile and stat_quantile.
conditional quantiles of y to calculate and display
formula relating y variables to x variables
Quantile regression method to use. Currently only supports rq.
List of additional arguments passed on to the modelling function defined by method.


This can be used as a continuous analogue of a geom_boxplot.


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

  • x
  • y
  • alpha
  • colour
  • linetype
  • size
  • weight

Computed variables

quantile of distribution


m <- ggplot(mpg, aes(displ, 1 / hwy)) + geom_point() m + geom_quantile()
Loading required package: SparseM Attaching package: ‘SparseM’ The following object is masked from ‘package:base’: backsolve Attaching package: ‘quantreg’ The following object is masked from ‘package:survival’: untangle.specials Smoothing formula not specified. Using: y ~ x

m + geom_quantile(quantiles = 0.5)
Smoothing formula not specified. Using: y ~ x

q10 <- seq(0.05, 0.95, by = 0.05) m + geom_quantile(quantiles = q10)
Smoothing formula not specified. Using: y ~ x

# You can also use rqss to fit smooth quantiles m + geom_quantile(method = "rqss")
Smoothing formula not specified. Using: y ~ qss(x, lambda = 1)

# Note that rqss doesn't pick a smoothing constant automatically, so # you'll need to tweak lambda yourself m + geom_quantile(method = "rqss", lambda = 0.1)
Smoothing formula not specified. Using: y ~ qss(x, lambda = 0.1)

# Set aesthetics to fixed value m + geom_quantile(colour = "red", size = 2, alpha = 0.5)
Smoothing formula not specified. Using: y ~ x