plot.calibration_simplex: Plot Calibration Simplex

Description

Plot Calibration Simplex

Usage

# S3 method for calibration_simplex
plot(
  x,
  true_error = TRUE,
  error_scale = 0.3,
  min_bin_freq = 10,
  plot_error_scale = TRUE,
  scale_area = NULL,
  indicate_bins = TRUE,
  category_labels = c("1", "2", "3"),
  use_pvals = FALSE,
  alphas = c(0.1, 0.01),
  colors = c("blue", "orange", "red", "black"),
  ...
)

Arguments

x: Object of class calibration_simplex
true_error: Logical, specifying whether to use true miscalibration errors or approximate miscalibration errors.
error_scale: A number specifying the magnitude of the miscalibration errors (greater 0, usually should be less than 1, cf. note below).
min_bin_freq: A number. Lower bound for (absolute) frequencies, i.e. how many observations have to lie in a bin for it to be plotted.
plot_error_scale: Logical, specifying whether to plot a scale showing the magnitude of miscalibration errors.
scale_area: Optional. A number by which the areas of the points are scaled. Use if points are to small or to big.
indicate_bins: Logical, specifying whether to connect points to their respective bin (center of hexagon).
category_labels: A vector of length 3 containing the category names, e.g. c("1","2","3") (default)
use_pvals: Logical, determines whether multinomial p-values are used for uncertainty quantification, see details.
alphas: Vector of length 2 with values 1 > alphas[1] > alphas[2] >= 0.0001. Only relevant if use_pvals = TRUE.
colors: Vector of length 4 specifying colors, defaults to c("blue","orange","red","black"). Coloring used for p-values, see details. Only relevant if use_pvals = TRUE.
...: Arguments concerning the title (e.g. main, cex.main, col.main and font.main) and subtitle (e.g. sub, cex.sub, col.sub and font.sub) may be passed here.

Details

If multinomial p-values are used (use_pvals = TRUE), the dots are colored in the following way:

colors[1] (blue by default): p-value greater alphas[1] (0.1 by default).
colors[2] (orange by default): p-value between alphas[1] and alphas[2] (0.1 and 0.01 by default)
colors[3] (red by default): p-value less than alphas[2] (0.01 by default)
colors[4] (black by default): p-value is exactly 0. This only happens if a category which is assigned 0 probability realizes.

Many small p-values (orange and red dots) indicate miscalibrated predictions, whereas many blue dots indicate that the predictions may in fact be calibrated. WARNING: The use of the multinomial p-values is more of an experimental feature and may not yield reliable p-values, especially if n is small. For details regarding the calculation of the p-values see also calibration_simplex.