density_bins: Density bins and histogram bins as data frames

In mjskay/tidybayes: Tidy Data and 'Geoms' for Bayesian Models

Density bins and histogram bins as data frames

Description

Generates a data frame of bins representing the kernel density (or histogram) of a vector, suitable for use in generating predictive distributions for visualization. These functions were originally designed for use with the now-deprecated predict_curve(), and may be deprecated in the future.

Usage

density_bins(x, n = 101, ...)

histogram_bins(x, n = 30, breaks = n, ...)

Arguments

x	A numeric vector
n	Number of bins
...	Additional arguments passed to density() or hist().
breaks	Used to set bins for histogram_bins. Can be number of bins (by default it is set to the value of n) or a method for setting bins. See the breaks argument of hist().

Details

These functions are simple wrappers to density() and hist() that compute density estimates and return their results in a consistent format: a data frame of bins suitable for use with the now-deprecated predict_curve().

density_bins computes a kernel density estimate using density().

histogram_bins computes a density histogram using hist().

Value

A data frame representing bins and their densities with the following columns:

mid	Bin midpoint
lower	Lower endpoint of each bin
upper	Upper endpoint of each bin
density	Density estimate of the bin

Author(s)

Matthew Kay

See Also

See add_predicted_draws() and stat_lineribbon() for a better approach. These functions may be deprecated in the future.

Examples

## Not run: 

library(ggplot2)
library(dplyr)
library(brms)
library(modelr)

theme_set(theme_light())

m_mpg = brm(mpg ~ hp * cyl, data = mtcars)

step = 1
mtcars %>%
  group_by(cyl) %>%
  data_grid(hp = seq_range(hp, by = step)) %>%
  add_predicted_draws(m_mpg) %>%
  summarise(density_bins(.prediction), .groups = "drop") %>%
  ggplot() +
  geom_rect(aes(
    xmin = hp - step/2, ymin = lower, ymax = upper, xmax = hp + step/2,
    fill = ordered(cyl), alpha = density
  )) +
  geom_point(aes(x = hp, y = mpg, fill = ordered(cyl)), shape = 21, data = mtcars) +
  scale_alpha_continuous(range = c(0, 1)) +
  scale_fill_brewer(palette = "Set2")


## End(Not run)

mjskay/tidybayes documentation built on Sept. 10, 2023, 5:20 a.m.