geom_interval: Line plot visualising intervals of a distribution
In ggfan: Summarise a Distribution Through Coloured Intervals

Description Usage Arguments Aesthetics See Also Examples

For every value of x, computes quantiles of y and uses these to plot intervals containing increasing proportions of the total density of y. Boundaries of intervals are mapped to linetype. Quantiles can also be precomputed and mapped to the aesthetic quantile. This function is designed with the need to summarise MCMC posterior distributions in mind.

geom_interval(mapping = NULL, data = NULL, stat = "interval_fctr",
  position = "identity", intervals = c(0, 50, 90)/100,
  lineend = "butt", linejoin = "round", linemitre = 1,
  arrow = NULL, na.rm = FALSE, show.legend = NA,
  inherit.aes = TRUE, ...)

`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.
`stat`	Use to override the default use of `stat_interval`
`position`	Position adjustment, either as a string, or the result of a call to a position adjustment function.
`intervals`	specify the collection of intervals to be represented in the fan.
`lineend`	Line end style (round, butt, square).
`linejoin`	Line join style (round, mitre, bevel).
`linemitre`	Line mitre limit (number greater than 1).
`arrow`	Arrow specification, as created by `grid::arrow()`.
`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()`.
`...`	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.

geom_interval understands the following aesthetics (required aesthetics are in bold):

x
y
quantile
group
colour
size

stat_summary Summarises y at each value of x stat_quantile Uses quantile regression to predict quantiles geom_fan Plot intervals on a continuous colour scale

library(ggplot2)
# Basic use. The data frame must have multiple y values for each
# x
ggplot(fake_df, aes(x=x,y=y)) +geom_interval()


# use precomputed quantiles - reducing storage requirements.
intervals = c(0,50,90)/100
fake_q <- calc_quantiles(fake_df, intervals=intervals)
# intervals in geom_fan must be the same as used to compute quantiles.
ggplot(fake_q, aes(x=x,y=y, quantile=quantile)) +
 geom_interval(intervals=intervals)