stat_rollingkernel {ggh4x} | R Documentation |
Rolling Kernel
Description
A rolling kernel moves along one of the axes and assigns weights to
datapoints depending on the distance to the kernel's location. It then
calculates a weighted average on the y-values of the datapoints, creating a
trendline. In contrast to (weighted) rolling averages, the interval between
datapoints do not need to be constant.
Usage
stat_rollingkernel(
mapping = NULL,
data = NULL,
geom = "line",
position = "identity",
...,
bw = "nrd",
kernel = "gaussian",
n = 256,
expand = 0.1,
na.rm = FALSE,
orientation = "x",
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 |
Use to override the default geom ("line" ).
|
position |
Position adjustment, either as a string naming the adjustment
(e.g. "jitter" to use position_jitter ), or the result of a call to a
position adjustment function. Use the latter if you need to change the
settings of the adjustment.
|
... |
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.
|
bw |
A bandwidth, which can be one of the following:
A
numeric of length one indicating a measure of kernel width, in data
units.
A rel object of length one constructed for setting a
bandwidth relative to the group data range. Can be constructed with the
rel() function.
A character of length one, naming one
of the functions documented in bw.nrd() .
|
kernel |
One of the following:
A function that
takes a vector of distances as first argument, a numeric bandwidth as
second argument and returns relative weights.
A character of
length one that can take one of the following values:
"gaussian" or "norm" A kernel that follows a normal
distribution with 0 mean and bandwidth as standard deviation.
"mean" or "unif" A kernel that follows a uniform
distribution with bandwidth * -0.5 and bandwidth * 0.5 as
minimum and maximum. This is similar to a simple, unweighted moving
average.
"cauchy" A kernel that follows a Cauchy
distribution with 0 as location and bandwidth as scale parameters. The
Cauchy distribution has fatter tails than the normal distribution.
|
n |
An integer of length one: how many points to return per
group.
|
expand |
A numeric of length one: how much to expand the range
for which the rolling kernel is calculated beyond the most extreme
datapoints.
|
na.rm |
If FALSE , the default, missing values are removed with
a warning. If TRUE , missing values are silently removed.
|
orientation |
A character of length one, either "x"
(default) or "y" , setting the axis along which the rolling should
occur.
|
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() .
|
Value
A Layer ggproto object.
Aesthetics
stat_rollingkernel()
understands the following
aesthetics (required aesthetics are in bold)
Computed variables
x
A sequence of ordered x positions.
y
The weighted value of the rolling kernel.
weight
The sum of weight strengths at a position.
scaled
The fraction of weight strengths at a position. This is
the same as weight / sum(weight)
by group.
Examples
ggplot(mpg, aes(displ, hwy, colour = class)) +
geom_point() +
stat_rollingkernel()
# The (scaled) weights can be used to emphasise data-dense areas
ggplot(mpg, aes(displ, hwy, colour = class)) +
geom_point() +
stat_rollingkernel(aes(alpha = after_stat(scaled)))
[Package
ggh4x version 0.2.8
Index]