A kernel density estimate, useful for displaying the distribution of variables with underlying smoothness.

geom_bkde(mapping = NULL, data = NULL, stat = "bkde",
  position = "identity", bandwidth = NULL, range.x = NULL,
  na.rm = FALSE, show.legend = NA, inherit.aes = TRUE, ...)

stat_bkde(mapping = NULL, data = NULL, geom = "area",
  position = "stack", kernel = "normal", canonical = FALSE,
  bandwidth = NULL, gridsize = 410, range.x = NULL,
  truncate = TRUE, na.rm = FALSE, show.legend = NA,
  inherit.aes = TRUE, ...)

Arguments

mapping

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.

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.

position

Position adjustment, either as a string, or the result of a call to a position adjustment function.

bandwidth

the kernel bandwidth smoothing parameter. see bkde for details. If NULL, it will be computed for you but will most likely not yield optimal results.

range.x

vector containing the minimum and maximum values of x at which to compute the estimate. see bkde for details

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().

...

Other arguments passed on to layer(). These are often aesthetics, used to set an aesthetic to a fixed value, like colour = "red" or size = 3. They may also be parameters to the paired geom/stat.

geom, stat

Use to override the default connection between geom_bkde and stat_bkde.

kernel

character string which determines the smoothing kernel. see bkde for details

canonical

logical flag: if TRUE, canonically scaled kernels are used. see bkde for details

gridsize

the number of equally spaced points at which to estimate the density. see bkde for details.

truncate

logical flag: if TRUE, data with x values outside the range specified by range.x are ignored. see bkde for details

Details

A sample of the output from geom_bkde(): Figure: geombkde01.png

Aesthetics

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

  • x

  • y

  • alpha

  • color

  • fill

  • linetype

  • size

Computed variables

density

density estimate

count

density * number of points - useful for stacked density plots

scaled

density estimate, scaled to maximum of 1

See also

See geom_histogram, geom_freqpoly for other methods of displaying continuous distribution. See geom_violin for a compact density display.

Examples

data(geyser, package="MASS") ggplot(geyser, aes(x=duration)) + stat_bkde(alpha=1/2)
#> Bandwidth not specified. Using '0.14', via KernSmooth::dpik.
ggplot(geyser, aes(x=duration)) + geom_bkde(alpha=1/2)
#> Bandwidth not specified. Using '0.14', via KernSmooth::dpik.
ggplot(geyser, aes(x=duration)) + stat_bkde(bandwidth=0.25)
ggplot(geyser, aes(x=duration)) + geom_bkde(bandwidth=0.25)