Functional boxplots for tf objects

Draw functional boxplots based on functional depth rankings.

Usage

stat_fboxplot(
  mapping = NULL,
  data = NULL,
  geom = "fboxplot",
  position = "identity",
  ...,
  orientation = NA,
  coef = 1.5,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE,
  depth = "MBD",
  depth_fn = NULL,
  fence_fn = NULL,
  central = 0.5,
  arg = NULL
)

geom_fboxplot(
  mapping = NULL,
  data = NULL,
  stat = "fboxplot",
  position = "identity",
  ...,
  outliers = TRUE,
  outlier.colour = NULL,
  outlier.color = NULL,
  outlier.fill = NULL,
  outlier.shape = NULL,
  outlier.size = NULL,
  outlier.stroke = 0.5,
  outlier.alpha = NULL,
  whisker.colour = NULL,
  whisker.color = NULL,
  whisker.linetype = NULL,
  whisker.linewidth = NULL,
  staple.colour = NULL,
  staple.color = NULL,
  staple.linetype = NULL,
  staple.linewidth = NULL,
  median.colour = NULL,
  median.color = NULL,
  median.linetype = NULL,
  median.linewidth = NULL,
  box.colour = NULL,
  box.color = NULL,
  box.linetype = NULL,
  box.linewidth = NULL,
  notch = FALSE,
  notchwidth = 0.5,
  staplewidth = 0,
  varwidth = FALSE,
  na.rm = FALSE,
  orientation = NA,
  show.legend = NA,
  inherit.aes = TRUE,
  depth = "MBD",
  depth_fn = NULL,
  fence_fn = NULL,
  central = 0.5,
  arg = NULL
)

Arguments

mapping, data, position, show.legend, inherit.aes, na.rm, orientation, ...

Passed on to ggplot2::layer().

coef

Inflation factor for the central envelope used to define outer fences, defaults to 1.5.

depth

Character scalar naming the built-in depth measure passed to tf::tf_depth() when depth_fn is NULL.

depth_fn

Optional custom depth function. Must return one numeric depth value per function.

fence_fn

Optional custom fence function. Must return a list with elements lower, upper, and outliers.

central

Fraction of deepest curves used to construct the central envelope. Defaults to 0.5.

arg

Optional evaluation grid used for depth calculation, envelopes, and drawing. Defaults to the natural grid of the mapped tf.

stat, geom

Use the functional boxplot stat/geom.

outliers

Should outlying curves be drawn?

outlier.colour, outlier.color, outlier.fill, outlier.shape, outlier.size

Styling parameters for outlier curves.

outlier.stroke

Accepted for interface compatibility with ggplot2::geom_boxplot() but ignored because functional outliers are drawn as curves.

outlier.alpha

Alpha used for outlier curves.

whisker.colour, whisker.color, whisker.linetype, whisker.linewidth

Styling parameters for fence lines.

staple.colour, staple.color, staple.linetype, staple.linewidth

Accepted for interface compatibility with ggplot2::geom_boxplot() but currently unused.

median.colour, median.color, median.linetype, median.linewidth

Styling parameters for the median curve.

box.colour, box.color, box.linetype, box.linewidth

Styling parameters for the central band outline.

notch, notchwidth, staplewidth, varwidth

Accepted for interface compatibility with ggplot2::geom_boxplot() but currently unused.

Value

A ggplot2 layer.

Details

stat_fboxplot() computes a median curve (thick line), a central region envelope (filled ribbon), functional fences (dashed lines), and optional outlying curves (defined as "exceeds the fences somewhere", plotted as solid lines) from a tf column. geom_fboxplot() draws these summaries as a band plus line layers.

The interface intentionally follows ggplot2::stat_boxplot() and ggplot2::geom_boxplot() where this is meaningful for functional data. Use aes(tf = f) to map a tf column. Separate functional boxplots inside a panel are defined by group, colour/color, or fill; separate panels are handled through facetting. Note that only color or fill need to be specified explicitly, as the other will be automatically mapped to the same variable if not provided.

Examples

# \donttest{
library(ggplot2)
set.seed(1312)
data <- data.frame(id = 1:50, grp = rep(c("A", "B"), each = 25))
data$f <- tf_rgp(50) + 5 * (data$grp == "A")

tf_ggplot(data, aes(tf = f, fill = grp)) + # same as `colour = grp` here!
  geom_fboxplot(alpha = 0.3)


tf_ggplot(data, aes(tf = f)) +
  geom_fboxplot(orientation = "y")

# }