HDR plot

Produces a 1d or 2d box plot of HDR regions. The darker regions contain observations with higher probability, while the lighter regions contain points with lower probability. Observations outside the largest HDR are shown as individual points. Anomalies with leave-one-out surprisal probabilities less than 0.005 are optionally shown in black.

Usage

gg_hdrboxplot(
  data,
  var1,
  var2 = NULL,
  prob = c(0.5, 0.99),
  color = "#0072b2",
  show_points = FALSE,
  show_anomalies = TRUE,
  scatterplot = show_points,
  alpha = NULL,
  jitter = TRUE,
  ngrid = 501,
  ...
)

Arguments

data: A data frame or matrix containing the data.
var1: The name of the first variable to plot (a bare expression).
var2: Optionally, the name of the second variable to plot (a bare expression).
prob: A numeric vector specifying the coverage probabilities for the HDRs.
color: The base color to use for the mode. Colors for the HDRs are generated by whitening this color.
show_points: A logical argument indicating if a regular HDR plot is required (FALSE), or whether to show the individual observations in the same colors (TRUE).
show_anomalies: A logical argument indicating if the surprisal anomalies should be shown (in black). These are points with leave-one-out surprisal probability values less than 0.005, and which lie outside the 99% HDR region.
scatterplot: Equivalent to show_points. Included for compatibility with gg_bagplot().
alpha: Transparency of points. Ignored if show_points is FALSE. Defaults to min(1, 500/n), where n is the number of observations plotted.
jitter: A logical value indicating if the points should be vertically jittered for the 1d box plots to reduce overplotting.
ngrid: Number of grid points to use for the density function.
...: Other arguments passed to dist_kde.

Value

A ggplot object showing an HDR plot or scatterplot of the data.

Details

The original HDR boxplot proposed by Hyndman (1996), can be produced with show_anomalies = FALSE, jitter = FALSE, alpha = 1, and all other arguments set to their defaults.

References

Hyndman, R J (1996) Computing and Graphing Highest Density Regions, The American Statistician, 50(2), 120–126. https://robjhyndman.com/publications/hdr/

Author

Rob J Hyndman

Examples

df <- data.frame(x = c(rnorm(1000), rnorm(1000, 5, 1), 10))
gg_hdrboxplot(df, x, show_anomalies = TRUE)

cricket_batting |>
  filter(Innings > 20) |>
  gg_hdrboxplot(Average)

oldfaithful |>
  filter(duration < 7000, waiting < 7000) |>
  gg_hdrboxplot(duration, waiting, show_points = TRUE)