Provides primitives for visualizing distributions using 'ggplot2' that are particularly tuned for
visualizing uncertainty in either a frequentist or Bayesian mode. Both analytical distributions (such as
frequentist confidence distributions or Bayesian priors) and distributions represented as samples (such as
bootstrap distributions or Bayesian posterior samples) are easily visualized. Visualization primitives include
but are not limited to: points with multiple uncertainty intervals,
eye plots (Spiegelhalter D., 1999) ,
density plots, gradient plots, dot plots (Wilkinson L., 1999) ,
quantile dot plots (Kay M., Kola T., Hullman J., Munson S., 2016) ,
complementary cumulative distribution function
barplots (Fernandes M., Walls L., Munson S., Hullman J., Kay M., 2018) ,
and fit curves with multiple uncertainty ribbons.