densityarea densityarea website

R-CMD-check CRAN status pkgdown DOI

The package {ggdensity}¹ allows for plotting interpretable bivariate densities by using highest density ranges (HDRs). For example:

 library(tibble)
 library(ggplot2)
 library(ggdensity)
 
 set.seed(10)
df <- tibble(
 x = c(rnorm(100), rnorm(100, mean = 3)),
 y = c(rnorm(100), rnorm(100, mean = 3))
)
 
 ggplot(df, aes(x,y))+
 stat_hdr()

{densityarea} gives direct access to these HDRs, either as data frames or as simple features, for further analysis.

Installation

You can install {densityarea} from CRAN with:

 install.packages("densityarea")

Or you can install the development version from GitHub with:

 # install.packages("devtools")
devtools::install_github("JoFrhwld/densityarea")

Example

The use case the package was initially developed for was for estimating vowel space areas.

 library(densityarea)
 library(dplyr)
 library(tidyr)
 library(sf)
 
 data(s01)
 
 # initial data processing
 
s01 |> 
 mutate(lF1 = -log(F1),
 lF2 = -log(F2))->
 s01

To get this speaker’s vowel space area we can pass the data through dplyr::reframe()

s01 |> 
 reframe(
 density_area(lF2, lF1, probs = 0.8)
 )
 #> # A tibble: 1 ×ばつ 3
 #> level_id prob area
 #> <int> <dbl> <dbl>
 #> 1 1 0.8 0.406

Or, we could get the spatial polygon associated with the 80% probability level

s01 |> 
 reframe(
 density_polygons(lF2, lF1, probs = 0.8, as_sf = T)
 )
 #> # A tibble: 1 ×ばつ 3
 #> level_id prob geometry
 #> <int> <dbl> <POLYGON>
 #> 1 1 0.8 ((-7.777586 -6.009484, -7.801131 -6.010429, -7.824676 -6.01700...

For more

For more details on using {densityarea}, see , and for further information on using spatial polygons, see vignette("sf-operations").

Otto J, Kahle D (2023). ggdensity: Interpretable Bivariate Density Visualization with ‘ggplot2’. https://jamesotto852.github.io/ggdensity/ https://github.com/jamesotto852/ggdensity/ ↩︎