Generates a combination of a density and stat_pointintervalh
representing the density, point summary, and uncertainty intervals
for draws from a distribution. Useful for representing posteriors from Bayesian models;
in that context the mirrored version is variously called an eye plot, a raindrop plot,
violin plot; hence "half-eye" for this plot.
geom_halfeyeh(mapping = NULL, data = NULL, position = "identity",
trim = TRUE, scale = "area", relative_scale = 1, fill = NULL,
density.color = NA, ..., point_interval = median_qi,
fun.data = NULL, fun.args = list(), .width = c(0.66, 0.95), .prob,
color = NULL, size = NULL, size_domain = NULL, size_range = NULL,
fatten_point = NULL)The aesthetic mapping, usually constructed with
aes or aes_string. Only needs to be set at the
layer level if you are overriding the plot defaults.
A layer specific dataset - only needed if you want to override the plot defaults.
The position adjustment to use for overlapping points on this layer.
If TRUE (default),
trim the tails of the density to the range of the data. If FALSE,
don't trim the tails.
If "area" (default), all densities have the same area (before trimming the tails). If "count", areas are scaled proportionally to the number of observations. If "width", all densities have the same maximum width/height.
A relative scaling factor to determine how much of the available
space densities are scaled to fill: if 1, all available space is filled.
Fill color of the density.
Outline color of the density.
The default, NA, suppresses the density outline. Set to another value to set the density outline color
manually, or set to NULL if you want the outline color of the density to be determined by the aesthetic
mapping.
Currently unused.
A function that when given a vector should
return a data frame with variables y, ymin, ymax, and .width; or
x, xmin, xmax, and .width. Either is acceptable: output
will be converted into the x-based aesthetics geom_halfeyeh.
See the point_interval family of functions.
Similar to point_interval, for compatibility with stat_summary.
Note: if the summary function is passed using fun.data, the x and y-based aesthetics
are not converted to the correct form automatically.
Optional arguments passed to fun.data.
The .width argument passed to point_interval.
Deprecated. Use .width instead.
Passed to stat_pointintervalh. Color of the point
summary and uncertainty interval.
Passed to stat_pointintervalh. Line weight of the point
summary and uncertainty interval.
The minimum and maximum of the values of the size aesthetic that will be translated into actual
sizes drawn according to size_range (see the documentation for that argument, below.)
This geom scales the raw size aesthetic values, as they tend to be too thick when using the default
settings of scale_size_continuous, which give sizes with a range of c(1, 6). The
size_domain value indicates the input domain of raw size values (typically this should be equal to the value
of the range argument of the scale_size_continuous function), and size_range indicates
the desired output range of the size values (the min and max of the actual sizes used to draw intervals).
A multiplicative factor used to adjust the size of the point relative to the size of the thickest line.
A half-eye plot is a compact visual summary of the distribution of a sample, used (under various names and with subtle variations) to visualize posterior distributions in Bayesian inference. This instantiation is a combination of a density plot, point summary, and one or more uncertainty intervals.
geom_halfeyeh() is roughly equivalent to geom_density_ridges() + stat_pointintervalh()
with some reasonable defaults, including color choices and the use of median with 95%
and 66% quantile intervals.
See geom_eye and geom_eyeh for the mirrored-density
(full "eye") versions. See geom_density_ridges and stat_summaryh for the geoms
this function is based on.
# NOT RUN {
library(magrittr)
library(ggplot2)
data(RankCorr, package = "tidybayes")
RankCorr %>%
spread_draws(u_tau[i]) %>%
ggplot(aes(y = i, x = u_tau)) +
geom_halfeyeh()
# }
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