Plot empirical rate data as a density with the matching beta distribution

Compares empirical rate data to a beta distribution with the same mean and standard deviation.

PlotDistDensityBeta(
  frm,
  xvar,
  title,
  ...,
  curve_color = "lightgray",
  beta_color = "blue",
  mean_color = "blue",
  sd_color = "darkgray"
)

Arguments

frm	data frame to get values from
xvar	name of the independent (input or model) column in frame
title	title to place on plot
...	force later arguments to bind by name
curve_color	color for empirical density curve
beta_color	color for matching theoretical beta
mean_color	color for mean line
sd_color	color for 1-standard deviation lines (can be NULL)

Details

Plots the empirical density, the theoretical matching beta, the mean value, and plus/minus one standard deviation from the mean.

Examples

set.seed(52523)
N = 100
pgray = 0.1  # rate of gray horses in the population
herd_size = round(runif(N, min=25, 50))
ngray = rbinom(N, herd_size, pgray)
hdata = data.frame(n_gray=ngray, herd_size=herd_size)

# observed rate of gray horses in each herd
hdata$rate_gray = with(hdata, ngray/herd_size)

title = "Observed prevalence of gray horses in population"

PlotDistDensityBeta(hdata, "rate_gray", title) +
  ggplot2::geom_vline(xintercept = pgray, linetype=4, color="maroon") +
  ggplot2::annotate("text", x=pgray+0.01, y=0.01, hjust="left",
                    label = paste("True prevalence =", pgray))

# no sd lines
PlotDistDensityBeta(hdata, "rate_gray", title,
                    sd_color=NULL)