## ----setup, include = FALSE---------------------------------------------------
knitr::opts_chunk$set(collapse = TRUE, comment = "#>")
library(dceasimR)

## ----data---------------------------------------------------------------------
df <- tibble::tibble(
  group      = 1:5,
  mean_hale  = c(52.1, 56.3, 59.8, 63.2, 66.8),
  pop_share  = rep(0.2, 5)
)

## ----sii----------------------------------------------------------------------
calc_sii(df, "mean_hale", "group", "pop_share")

## ----rii----------------------------------------------------------------------
calc_rii(df, "mean_hale", "group", "pop_share")

## ----ci-----------------------------------------------------------------------
calc_concentration_index(df, "mean_hale", "group", "pop_share",
                          type = "standard")

## ----atkinson-----------------------------------------------------------------
calc_atkinson_index(df$mean_hale, df$pop_share, epsilon = 1)

## ----gini---------------------------------------------------------------------
calc_gini(df$mean_hale, df$pop_share)

## ----all----------------------------------------------------------------------
calc_all_inequality_indices(df, "mean_hale", "group", "pop_share",
                             epsilon_values = c(0.5, 1, 2))

## ----lorenz-data--------------------------------------------------------------
ld <- compute_lorenz_data(df$mean_hale, df$pop_share, "England 2019")

## ----lorenz-plot, fig.width = 5, fig.height = 4-------------------------------
library(ggplot2)
ggplot(ld, aes(cum_pop, cum_health)) +
  geom_line(colour = "steelblue", linewidth = 1) +
  geom_abline(linetype = "dashed") +
  labs(x = "Cumulative population", y = "Cumulative health",
       title = "Lorenz Curve") +
  theme_minimal()