Uncertainty marks (slab + interval) — mark

Marks for visualising a distribution's shape and its summary intervals together, in the style of the ggdist package — a natural fit for posterior draws or bootstrap samples (one row per draw, grouped by a categorical x).

Usage

mark_halfeye(
  plot,
  ...,
  .width = c(0.66, 0.95),
  point = "median",
  adjust = 1,
  scale = 0.9,
  blend = NULL,
  sketch = NULL,
  data = NULL
)

mark_interval(
  plot,
  ...,
  .width = c(0.66, 0.95),
  point = "median",
  blend = NULL,
  data = NULL
)

Arguments

plot: A PlotSpec (from vplot()).
...: Encodings (tidy-eval): a categorical x and the sample y (+ color/fill).
.width: Interval probabilities, widest last (default c(0.66, 0.95)).
point: Central summary: "median" (default) or "mean".
adjust: mark_halfeye() density bandwidth multiplier.
scale: Slab width as a fraction of the category band (mark_halfeye()).
blend: Optional blend mode for compositing this layer against what is already drawn beneath it (the panel and earlier layers), one of the CSS mix-blend-mode names, e.g. "multiply", "screen", "darken". The whole layer composites as one isolated group (not per element).
sketch: A sketch() spec giving this layer a hand-drawn look (wobbly outlines, hachure fills), NA/FALSE to force it crisp (overriding a plot-wide theme_sketch()), or NULL (default) to inherit. Geometry marks accept it; text, raster, hex and datashade marks do not.
data: Optional layer data frame; overrides the plot data for this layer.

Value

The modified PlotSpec.

Details

mark_halfeye() draws, per x category, a one-sided density "slab" (a half violin) with a point-interval at its base: the median (or mean) as a point, a thick bar for the inner interval and a thin bar for the outer one.
mark_interval() draws the point-interval alone (no slab).

Intervals are equal-tailed quantile intervals at the .width probabilities (widest drawn thinnest). Supply many draws per x (e.g. posterior samples).

Examples

set.seed(1)
draws <- data.frame(
  grp = rep(c("a", "b", "c"), each = 400),
  val = rnorm(1200, rep(c(0, 1, 2), each = 400))
)
vplot(draws) |> mark_halfeye(x = grp, y = val)

vplot(draws) |> mark_interval(x = grp, y = val)