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Areas of Bivarate Density Distributions
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JoFrhwld/densityarea
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The package{ggdensity}1 allows for plotting interpretablebivariate 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 framesor assimple features, for furtheranalysis.
You can install{densityarea} from CRAN with:
install.packages("densityarea")Or you can install the development version fromGitHub with:
# install.packages("devtools")devtools::install_github("JoFrhwld/densityarea")
The use case the package was initially developed for was for estimatingvowel space areas.
library(densityarea)library(dplyr)library(tidyr)library(sf)data(s01)# initial data processings01|> mutate(lF1=-log(F1),lF2=-log(F2))->s01
To get this speaker’s vowel space area we can pass the data throughdplyr::reframe()
s01|> reframe( density_area(lF2,lF1,probs=0.8) )#> # A tibble: 1 × 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% probabilitylevel
s01|> reframe( density_polygons(lF2,lF1,probs=0.8,as_sf=T) )#> # A tibble: 1 × 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 details on using{densityarea}, see , and for furtherinformation on using spatial polygons, seevignette("sf-operations").
Footnotes
Otto J, Kahle D (2023).ggdensity: Interpretable BivariateDensity Visualization with ‘ggplot2’.https://jamesotto852.github.io/ggdensity/https://github.com/jamesotto852/ggdensity/↩
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