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

## ----ede----------------------------------------------------------------------
health  <- c(52.1, 56.3, 59.8, 63.2, 66.8)
weights <- rep(0.2, 5)

# eta = 0: no inequality aversion (arithmetic mean)
calc_ede(health, weights, eta = 0)

# eta = 1: moderate aversion (geometric mean)
calc_ede(health, weights, eta = 1)

# eta = 5: strong aversion
calc_ede(health, weights, eta = 5)

## ----profile, fig.width = 6, fig.height = 4-----------------------------------
profile <- calc_ede_profile(health, weights, eta_range = seq(0, 10, 0.1))
library(ggplot2)
ggplot(profile, aes(eta, ede)) +
  geom_line(colour = "steelblue", linewidth = 1) +
  labs(x = expression(eta), y = "EDE (years)",
       title = "EDE Profile") +
  theme_minimal()

## ----weights------------------------------------------------------------------
ew <- calc_equity_weights(health, weights, eta = 1)
ew  # Q1 (most deprived) gets highest weight

## ----swf----------------------------------------------------------------------
post_health <- health + c(0.5, 0.6, 0.5, 0.4, 0.3)
calc_social_welfare(health, post_health, weights, eta = 1)

