ggdist: stat_interval – R documentation

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stat_interval

Multiple uncertainty interval plots (ggplot stat)

Description

A combination of stat_sample_slabinterval() and geom_slabinterval() with sensible defaults. While the corresponding geoms are intended for use on data frames that have already been summarized using a point_interval() function, these stats are intended for use directly on data frames of draws, and will perform the summarization using a point_interval() function.

Usage

stat_interval(
  mapping = NULL,
  data = NULL,
  geom = "interval",
  position = "identity",
  ...,
  orientation = NA,
  interval_function = NULL,
  interval_args = list(),
  point_interval = median_qi,
  .width = c(0.5, 0.8, 0.95),
  show_point = FALSE,
  show_slab = FALSE,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE,
  .prob,
  fun.data,
  fun.args
)

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. A `function` can be created from a `formula` (e.g. `~ head(.x, 10)`).
`geom`	Use to override the default connection between `stat_slabinterval` and `geom_slabinterval()`
`position`	Position adjustment, either as a string, or the result of a call to a position adjustment function.
`...`	Other arguments passed to `layer()`. They may also be arguments to the paired geom (e.g., `geom_pointinterval()`)
`orientation`	Whether this geom is drawn horizontally (`"horizontal"`) or vertically (`"vertical"`). The default, `NA`, automatically detects the orientation based on how the aesthetics are assigned, and should generally do an okay job at this. When horizontal (resp. vertical), the geom uses the `y` (resp. `x`) aesthetic to identify different groups, then for each group uses the `x` (resp. `y`) aesthetic and the `thickness` aesthetic to draw a function as an slab, and draws points and intervals horizontally (resp. vertically) using the `xmin`, `x`, and `xmax` (resp. `ymin`, `y`, and `ymax`) aesthetics. For compatibility with the base ggplot naming scheme for `orientation`, `"x"` can be used as an alias for `"vertical"` and `"y"` as an alias for `"horizontal"` (tidybayes had an `orientation` parameter before ggplot did, and I think the tidybayes naming scheme is more intuitive: `"x"` and `"y"` are not orientations and their mapping to orientations is, in my opinion, backwards; but the base ggplot naming scheme is allowed for compatibility).
`interval_function`	Custom function for generating intervals (for most common use cases the `point_interval` argument will be easier to use). This function takes a data frame of aesthetics and a `.width` parameter (a vector of interval widths), and returns a data frame with columns `.width` (from the `.width` vector), `.value` (point summary) and `.lower` and `.upper` (endpoints of the intervals, given the `.width`). Output will be converted to the appropriate `x`- or `y`-based aesthetics depending on the value of `orientation`. If `interval_function` is `NULL`, `point_interval` is used instead.
`interval_args`	Additional arguments passed to `interval_function` or `point_interval`.
`point_interval`	A function from the `point_interval()` family (e.g., `median_qi`, `mean_qi`, etc). This function should take in a vector of value, and should obey the `.width` and `.simple_names` parameters of `point_interval()` functions, such that when given a vector with `.simple_names = TRUE` should return a data frame with variables `.value`, `.lower`, `.upper`, and `.width`. Output will be converted to the appropriate `x`- or `y`-based aesthetics depending on the value of `orientation`. See the `point_interval()` family of functions for more information.
`.width`	The `.width` argument passed to `interval_function` or `point_interval`.
`show_point`	Should the point portion of the geom be drawn? Default `TRUE`.
`show_slab`	Should the slab portion of the geom be drawn? Default `TRUE`.
`na.rm`	If `FALSE`, the default, missing values are removed with a warning. If `TRUE`, missing values are silently removed.
`show.legend`	Should this layer be included in the legends? Default is `c(size = FALSE)`, unlike most geoms, to match its common use cases. `FALSE` hides all legends, `TRUE` shows all legends, and `NA` shows only those that are mapped (the default for most geoms).
`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()`.
`.prob`	Deprecated. Use `.width` instead.
`fun.data`	Deprecated. Use `point_interval` or `interval_function` instead.
`fun.args`	Deprecated. Use `interval_args` instead.

Value

A ggplot2::Stat representing a multiple interval geometry which can be added to a ggplot() object.

Aesthetics

These stats support the following aesthetics:

colour
datatype
x
y
thickness
group

In addition, in their default configuration (paired with geom_interval()) the following aesthetics are supported by the underlying geom:

x
y
datatype
alpha
colour
colour_ramp
linetype
fill
shape
stroke
point_colour
point_fill
point_alpha
point_size
size
interval_colour
interval_alpha
interval_size
interval_linetype
slab_size
slab_colour
slab_fill
slab_alpha
slab_linetype
fill_ramp
ymin
ymax
xmin
xmax
width
height
thickness
group

See examples of some of these aesthetics in action in vignette("slabinterval"). Learn more about the sub-geom aesthetics (like interval_color) in the scales documentation. Learn more about basic ggplot aesthetics in vignette("ggplot2-specs").

Examples

library(dplyr)
library(ggplot2)

theme_set(theme_ggdist())

data(RankCorr_u_tau, package = "ggdist")

RankCorr_u_tau %>%
  group_by(i) %>%
  ggplot(aes(y = factor(i), x = u_tau)) +
  stat_interval() +
  scale_color_brewer()

RankCorr_u_tau %>%
  group_by(i) %>%
  ggplot(aes(x = factor(i), y = u_tau)) +
  stat_interval() +
  scale_color_brewer()

ggdist

Visualizations of Distributions and Uncertainty

v2.4.0

GPL (>= 3)

Authors

Matthew Kay [aut, cre]

Initial release

2021-01-03