Display a fan plot

A fan plot consist of a set of transparent ribbons each representing a different coverage of the uncertainty around an estimate. The coverages are based on the assumption of a normal distribution with mean link(y) and standard error link_sd.

stat_fan(mapping = NULL, data = NULL, position = "identity",
  na.rm = FALSE, show.legend = NA, inherit.aes = TRUE,
  geom = "ribbon", ..., fine = FALSE, link = c("identity", "log",
  "logit"))

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)).
position

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

Use a different geom than the default "ribbon".
...

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.
fine

a logical value. TRUE displays coverages from 10% to 90% in steps of 10%. FALSE displays coverages from 30% to 90% in steps of 30%. Defaults to FALSE
link

the link function to apply on the y before calculting the coverage intervals. Note that link_sd is the standard error on the link scale, while y is on the natural scale. Defaults to 'identify' which implies no transformation (link(y) == y). Other options are 'log' and 'logit'.

See also

Other ggplot2: scale_effect, stat_effect

Examples

set.seed(20191218)
z <- data.frame(
  year = 1990:2019,
  dx = rnorm(30, sd = 0.2),
  s = rnorm(30, 0.5, 0.01)
 )
z$index <- 3 + cumsum(z$dx)
library(ggplot2)
ggplot(z, aes(x = year, y = index, link_sd = s)) + stat_fan()
ggplot(z, aes(x = year, y = index, link_sd = s)) + stat_fan() + geom_line()
ggplot(z, aes(x = year, y = index, link_sd = s)) + stat_fan(fine = TRUE)
ggplot(z, aes(x = year, y = exp(index), link_sd = s)) +
  stat_fan(link = "log") + geom_line()
ggplot(z, aes(x = year, y = plogis(index), link_sd = s)) +
  stat_fan(link = "logit") + geom_line()
ggplot(z, aes(x = year, y = index, link_sd = s)) + stat_fan(geom = "rect")
ggplot(z, aes(x = year, y = index, link_sd = s)) + stat_fan(geom = "bar")
ggplot(z, aes(x = year, y = index, link_sd = s)) +
  stat_fan(geom = "errorbar")
ggplot(z, aes(x = year, y = index, link_sd = s)) +
  stat_fan(geom = "linerange")
ggplot(z, aes(x = year, y = index, link_sd = s)) +
  stat_fan(geom = "pointrange")

z <- expand.grid(year = 1990:2019, category = c("A", "B"))
z$dx <- rnorm(60, sd = 0.1)
z$index <- rep(c(0, 2), each = 30) + cumsum(z$dx)
z$s <- rnorm(60, rep(c(0.5, 1), each = 30), 0.05)
ggplot(z, aes(x = year, y = index, link_sd = s)) + stat_fan() + geom_line() +
  facet_wrap(~category)
ggplot(z, aes(x = year, y = index, link_sd = s)) +
  stat_fan(aes(fill = category)) + geom_line(aes(colour = category))