```
# generate vector (of incomes)
x <- c(541, 1463, 2445, 3438, 4437, 5401, 6392, 8304, 11904, 22261)
# compute Gini coefficient
Gini(x)
# working with weights
fl <- c(2.5, 7.5, 15, 35, 75, 150) # midpoints of classes
n <- c(25, 13, 10, 5, 5, 2) # frequencies
# with confidence intervals
Gini(x=fl, weights=n, conf.level=0.95, unbiased=FALSE)
# some special cases
x <- c(10, 10, 0, 0, 0)
plot(Lc(x))
Gini(x, unbiased=FALSE)
# the same with weights
Gini(x=c(10, 0), weights=c(2,3), unbiased=FALSE)
# perfect balance
Gini(c(10, 10, 10))
```

Run the code above in your browser using DataLab