Are densities from distributional incorrectly scaled?

[bjoernholzhauer]

The density that gets plotted e.g. for a standard normal when I use distributions from the distributional package seems to mismatch (in terms of scaling of the density, the shape of the density seems okay) what I manually calculate as pdf values. Because distributional appears to (in the example below) calculate the density correctly, I'm wondering whether this is a ggdist problem.

Simple example:

library(tidyverse)
library(distributional)
library(ggdist)

dnorm(x=0)
density(x = dist_normal(0, 1), q=0) # Matches the base R result from the line above (0.3989423)

# Produces the plot below (seems to have the density at 0 near 0.83 or so?)
tibble(mu=0, sd=1) %>% 
  ggplot(aes(xdist=dist_normal(mu=mu, sigma=sd))) + 
  stat_halfeye()

This is with R version 4.3.1 (2023-06-16 ucrt) on Windows 10, distributional version 0.3.2 and ggdist version 3.3.0 - i.e. latest version on CRAN as per today).

[mjskay]

The y axis labels will not correspond to density values because slabs in ggdist map densities onto a thickness aesthetic, which is scaled to fit between other values placed on the y axis (e.g. so that when the y axis is categorical slabs can be displayed at each y value).

This scaling is controlled by the normalize parameter and the scale aesthetic (see here); if you want thickness values to match up with y values, you could do something like:

ggplot() + 
  ggdist::stat_slab(aes(xdist = distributional::dist_normal(0, 1)), scale = 1, normalize = "none")

But this disables any guarantees that the slab will fit within the space allocated to it.

At some point labeling the thickness values will be made easier by #183, which should be a better solution to this problem.

[mjskay]

See also #52 or the second diagram in the slabinterval vignette

[mjskay]

There is now a prototype implementation of a solution to this on the subguide branch. See this comment: #183 (comment)