geom_bkde | R Documentation |
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,
...
)
mapping |
Set of aesthetic mappings created by |
data |
The data to be displayed in this layer. There are three options: If A A |
position |
Position adjustment, either as a string naming the adjustment
(e.g. |
bandwidth |
the kernel bandwidth smoothing parameter. see
|
range.x |
vector containing the minimum and maximum values of x at which
to compute the estimate. see |
na.rm |
If |
show.legend |
logical. Should this layer be included in the legends?
|
inherit.aes |
If |
... |
Other arguments passed on to |
geom, stat |
Use to override the default connection between
|
kernel |
character string which determines the smoothing kernel. see
|
canonical |
logical flag: if TRUE, canonically scaled kernels are used.
see |
gridsize |
the number of equally spaced points at which to estimate the
density. see |
truncate |
logical flag: if TRUE, data with x values outside the range
specified by range.x are ignored. see |
A sample of the output from geom_bkde()
:
geom_bkde
understands the following aesthetics (required aesthetics
are in bold):
x
y
alpha
color
fill
linetype
size
density estimate
density * number of points - useful for stacked density plots
density estimate, scaled to maximum of 1
See geom_histogram
, geom_freqpoly
for
other methods of displaying continuous distribution.
See geom_violin
for a compact density display.
data(geyser, package="MASS")
ggplot(geyser, aes(x=duration)) +
stat_bkde(alpha=1/2)
ggplot(geyser, aes(x=duration)) +
geom_bkde(alpha=1/2)
ggplot(geyser, aes(x=duration)) +
stat_bkde(bandwidth=0.25)
ggplot(geyser, aes(x=duration)) +
geom_bkde(bandwidth=0.25)
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