Generate outcome draws from a smooth fit

Generate outcome draws from a smooth fit. This stat is similar to stat_smooth(), but there are a few important differences. First, there is no method argument. Only smooth fits fitted via mgcv::gam() are currently supported. If you want a linear fit, set a linear formula via formula = y ~ x. Second, there is no se argument. This stat cannot draw confidence bands. See confidence_band() for a workaround if you want to add confidence bands. Internally, the stat uses the function sample_outcomes() to calculate outcomes.

stat_smooth_draws(mapping = NULL, times = 10, data = NULL,
  geom = "smooth", position = "identity", ..., formula = y ~ s(x, bs
  = "cs"), n = 80, fullrange = FALSE, gam.args = list(method =
  "REML"), na.rm = FALSE, show.legend = NA, inherit.aes = TRUE)

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.
times	Number of outcomes to draw.
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.
geom	Use to override the default connection between `geom_smooth()` and `stat_smooth()`.
position	Position adjustment, either as a string, or the result of a call to a position adjustment function.
...	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.
formula	Formula to use in smoothing function. Default is a cubic spline, `y ~ s(x, bs = "cs")`. To generate a linear fit, set `formula = y ~ x`.
n	Number of points at which to evaluate smoother.
fullrange	Should the fit span the full range of the plot, or just the data?
gam.args	List of additional arguments passed on to the GAM call.
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()`.

Details

This stat fits the gam with Restricted Maximum Likelihood (REML) and uses the smoothing parameter uncertainty corrected covariance matrix to generate outcomes (unconditional = TRUE in sample_outcomes()). If you choose a different gam fitting method the stat sets unconditional = FALSE.

Note that for static plots, you will generally have to set the group aesthetic appropriately (e.g., aes(group = stat(.draw))). However, for animated plots you will normally not want to set the group aesthetic in this way. To enable animations by default, stat_smooth_draws() does not set a group aesthetic. See examples for further details.

Examples

library(ggplot2)

# static plots, need to set group aesthetic manually
ggplot(mtcars, aes(hp, mpg)) +
  geom_point() +
  stat_smooth_draws(aes(group = stat(.draw)), size = 0.5) +
  theme_bw()

# if we want to group by multiple variables, we have to use their
# mapped name (here, `colour` instead of `Species`) because we're
# creating the groups after after initial data mapping
ggplot(iris, aes(Sepal.Length, Sepal.Width, colour = Species)) +
  geom_point() +
  stat_smooth_draws(
    formula = y ~ x,
    aes(group = interaction(stat(.draw), colour)),
    size = 0.5
  ) +
  theme_bw()

# NOT RUN {
# animated plots
library(gganimate)

ggplot(mtcars, aes(hp, mpg)) +
  geom_point() +
  stat_smooth_draws(size = 0.5) +
  transition_states(stat(.draw), 1, 2)

ggplot(iris, aes(Sepal.Length, Sepal.Width, colour = Species)) +
  geom_point() +
  stat_smooth_draws(formula = y ~ x, times = 20, size = 0.5) +
  transition_states(stat(.draw), 1, 2)
# }

Arguments

Details

Examples

Contents