Aids the eye in seeing patterns in the presence of overplotting. geom_smooth() and stat_smooth() are effectively aliases: they both use the same arguments. Use stat_smooth() if you want to display the results with a non-standard geom.

 "mapping" = null,
 "data" = null,
 "stat" = "smooth",
 "position" = "identity",
 "method" = null,
 "formula" = null,
 "se" = true,
 "na.rm" = false,
 "orientation" = NA,
 "show.legend" = NA,
 "inherit.aes" = true

 "mapping" = null,
 "data" = null,
 "geom" = "smooth",
 "position" = "identity",
 "method" = null,
 "formula" = null,
 "se" = true,
  n ="80",
 "span" = 0.75,
 "fullrange" = false,
 "level" = 0.95,
  method.args = list({}),
 "na.rm" = false,
 "orientation" = NA,
 "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 cxplot().

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)).


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.


Smoothing method (function) to use, accepts either NULL or a character vector, e.g. "lm", "glm", "gam", "loess" or a function, e.g. MASS::rlm or mgcv::gam, stats::lm, or stats::loess. "auto" is also accepted for backwards compatibility. It is equivalent to NULL.

For method = NULL the smoothing method is chosen based on the size of the largest group (across all panels). stats::loess() is used for less than 1,000 observations; otherwise mgcv::gam() is used with formula = y ~ s(x, bs = "cs") with method = "REML". Somewhat anecdotally, loess gives a better appearance, but is 𝑂(𝑁2) in memory, so does not work for larger datasets.

If you have fewer than 1,000 observations but want to use the same gam() model that method = NULL would use, then set method = "gam", formula = y ~ s(x, bs = "cs").


Formula to use in smoothing function, eg. y ~ x, y ~ poly(x, 2), y ~ log(x). NULL by default, in which case method = NULL implies formula = y ~ x when there are fewer than 1,000 observations and formula = y ~ s(x, bs = "cs") otherwise.


Display confidence interval around smooth? (TRUE by default, see level to control.)


If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.


The orientation of the layer. The default (NA) automatically determines the orientation from the aesthetic mapping. In the rare event that this fails it can be given explicitly by setting orientation to either "x" or "y". See the Orientation section for more detail.


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.


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_smooth() and stat_smooth().


Number of points at which to evaluate smoother.


Controls the amount of smoothing for the default loess smoother. Smaller numbers produce wigglier lines, larger numbers produce smoother lines. Only used with loess, i.e. when method = "loess", or when method = NULL (the default) and there are fewer than 1,000 observations.


Should the fit span the full range of the plot, or just the data?


Level of confidence interval to use (0.95 by default).


List of additional arguments passed on to the modelling function defined by method.


Calculation is performed by the (currently undocumented) predictdf() generic and its methods. For most methods the standard error bounds are computed using the predict() method -- the exceptions are loess(), which uses a t-based approximation, and glm(), where the normal confidence interval is constructed on the link scale and then back-transformed to the response scale.


This geom treats each axis differently and, thus, can thus have two orientations. Often the orientation is easy to deduce from a combination of the given mappings and the types of positional scales in use. Thus, cxplot will by default try to guess which orientation the layer should have. Under rare circumstances, the orientation is ambiguous and guessing may fail. In that case the orientation can be specified directly using the orientation parameter, which can be either "x" or "y". The value gives the axis that the geom should run along, "x" being the default orientation you would expect for the geom.


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












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

Computed variables

stat_smooth() provides the following variables, some of which depend on the orientation:

y or x

lower pointwise confidence interval around the mean

ymax or xmax

standard error


var cxp = new cxplot("canvas1", mpg, aes("displ", "hwy"));
// Instead of a loess smooth, you can use any other modelling function var cxp = new cxplot("canvas2", mpg, aes("displ", "hwy")); cxp.geom_point(); cxp.geom_smooth({"se":false, "method":"lm"});
// Smooths are automatically fit to each group (defined by categorical // aesthetics or the group aesthetic) and for each facet. var cxp = new cxplot("canvas3", mpg, aes("displ", "hwy", {"color": "class"})); cxp.geom_point(); cxp.geom_smooth({"se":false, "method":"lm"});
var cxp = new cxplot("canvas4", mpg, aes("displ", "hwy")); cxp.geom_point(); cxp.geom_smooth(); cxp.facet_wrap("drv");