dev/noteworthy-notes.md

In friendly/heplots: Visualizing Hypothesis Tests in Multivariate Linear Models

ggplot2: Labeling noteworthy points in scatterplots (geom_noteworthy)

An important feature of many statistical plots is the ability to label "unusual" or "noteworthy" observations such as those with large residuals, high leverage, or those outside a given confidence envelope in a QQ plot.

This feature is available, automatically, in the various plots produced by plot.lm() for a linear model, using the id.n argument (default: id.n = 3) and the labels.id argument that supplies the labels for the noteworthy points.

The function showLabels in the car package extends this considerably, providing a very general utility for identifying noteworthy points and labeling them in plots. The id.method argument for that function allows selection by Mahalanobis $D^2$, absolute deviation from the mean of X or Y, absolute value of residual, or even a call to an arbitrary function, like cooks.distance().

Unfortunately this idea is currently awkward to implement in ggplot2. My question is how to do something similar in ggplot2?

As an example, for a plot of the Penguins data, plotting bill_length against bill_depth, and labeling the points with largest $D^2$ in the full dataset, here's what I had to do:

data(peng, package = "heplots")
# use all numeric variables
DSQ <- heplots::Mahalanobis(peng[, 3:6])
noteworthy <- order(DSQ, decreasing = TRUE)[1:3] |> print()
#> [1] 283  10  35

# augment the dataset to add `note` variable for selecting labels
peng_plot <- peng |>
  tibble::rownames_to_column(var = "id") |> 
  mutate(note = id %in% noteworthy)

ggplot(peng_plot, 
       aes(x = bill_length, y = bill_depth,
           color = species, shape = species, fill=species)) +
  geom_point(aes(size=note), show.legend = FALSE) +
  scale_size_manual(values = c(1.5, 4)) +
  geom_text(data = subset(peng_plot, note==TRUE),
            aes(label = id),
            nudge_y = .4, color = "black", size = 5) +
  geom_smooth(method = "lm", formula = y ~ x,
              se=FALSE, linewidth=2) +
  stat_ellipse(geom = "polygon", level = 0.95, alpha = 0.1) +
  # theme_penguins() +
  theme_bw(base_size = 14) +
  theme(legend.position = "inside",
        legend.position.inside=c(0.85, 0.15))

What I'm looking for is something like a geom_noteworthy() function. It provides similar methods to select points to be identified in a plot, and a geom argument that controls how the identified points are labeled in a plot.

geom_noteworthy(method = c("dsq", "mahal", "x", "y", "r"),
                n =            # number of points to label,
                geom =         # e.g.,   "text", "label", "repel",
                ...)

To this end, I've written a compute function, heplots::noteworthy(x, y, n, method, ...) that tries to be very general, https://github.com/friendly/heplots/blob/master/R/noteworthy.R

friendly/heplots documentation built on June 12, 2025, 4:10 p.m.