In malcolmbarrett/ggecdf: Calculate Weighted and Unweighted 'ECDFs' for 'ggplot2'

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)

ggecdf

The goal of ggecdf is to easily create weighted and unweighted empirical cumulative distributions (ECDFs) in ggplot2

Installation

You can install the development version of ggecdf from GitHub with:

# install.packages("devtools")
devtools::install_github("malcolmbarrett/ggecdf")

Example

geom_ecdf() allows you to create ECDFs based on ggplot's stat_ecdf()

library(ggecdf)
library(ggplot2)
# dataset with weights
nhefs_weights <- tidysmd::nhefs_weights

ggplot(
  nhefs_weights,
  aes(x = smokeyrs, color = factor(qsmk))
) +
  geom_ecdf() +
  xlab("Smoking Years") +
  ylab("Proportion <= x (unweighted)")

Additionally, geom_ecdf() supports a weights aesthetic to calculate weighted ECDFs. For instance, here's the same variables weighted by an ATO weight:

ggplot(
  nhefs_weights,
  aes(x = smokeyrs, color = factor(qsmk))
) +
  geom_ecdf(aes(weights = w_ato)) +
  xlab("Smoking Years") +
  ylab("Proportion <= x (weighted)")