plot.rate_distribution_fit: Plot A Fitted Rate Distribution

In bifrost: Branch-Level Inference Framework for Recognizing Optimal Shifts in Traits

Plot A Fitted Rate Distribution

Description

Plot a fitted candidate distribution from fit_rate_distribution(). The current method supports the Gumbel candidate used by Berv et al. (2026). It can overlay a pointwise bootstrap band and bootstrap density curves when bootstrap_rate_distribution() has already stored bootstrap draws on x.

Usage

## S3 method for class 'rate_distribution_fit'
plot(
  x,
  model = c("gumbel"),
  bootstrap = NULL,
  bootstrap_curves = 120L,
  col = "#b01f2e",
  hist_col = "grey90",
  band_alpha = 0.14,
  curve_alpha = 0.08,
  data_density = TRUE,
  rug = TRUE,
  breaks = "FD",
  main = NULL,
  xlab = NULL,
  ylab = "Density",
  ...
)

Arguments

x	A rate_distribution_fit object.
model	Distribution model to plot. Currently only "gumbel" is supported.
bootstrap	NULL or logical. If NULL, draw the bootstrap overlay when precomputed draws for model are available. If TRUE, require precomputed draws from bootstrap_rate_distribution(). If FALSE, draw no bootstrap overlay.
bootstrap_curves	Number of precomputed bootstrap density curves to draw over the band. Set to 0 to draw only the band.
col	Color for the fitted density, bootstrap band, and bootstrap curves.
hist_col	Histogram fill color. A vector of colors is passed through to graphics::hist() and can color bins individually.
band_alpha, curve_alpha	Alpha values for the bootstrap band and individual bootstrap curves.
data_density	Logical; overlay the empirical kernel density.
rug	Logical; add a rug for the fitted data values.
breaks	Histogram breaks passed to graphics::hist().
main, xlab, ylab	Plot labels.
...	Additional arguments passed to graphics::hist().

Value

Invisibly returns a list with the x grid, fitted density, bootstrap densities, bootstrap band, and plotted parameter table.

Examples

if (requireNamespace("univariateML", quietly = TRUE) &&
    requireNamespace("evd", quietly = TRUE)) {
  fit <- fit_rate_distribution(c(1, 1.4, 1.9, 2.8, 4.1, 6.5), models = "gumbel")
  fit <- bootstrap_rate_distribution(fit, model = "gumbel", reps = 25, seed = 1)
  plot(fit, bootstrap_curves = 5)
}

bifrost documentation built on Nov. 5, 2026, 9:07 a.m.