lorenz: Plots the (generalized) Lorenz Curve.

In wsteenbeek/lorenzgini: Lorenz Curve and Gini Calculation for when # events < # units of analysis

Description

This function plots a Lorenz curve. Following 'Bernasco, W. and W. Steenbeek (2017). More places than crimes: Implications for evaluating the law of crime concentration at place. Journal of Quantitative Criminology. https://doi.org/10.1007/s10940-016-9324-7', if # events < # units of analysis, vertical lines are added to the plot to indicate the percentage of units of analysis where events could occur under maximum equality.

Usage

lorenz(mydata, prop = TRUE, rescale = FALSE)

Arguments

mydata	a vector of N units, with counts of events per unit. The vector should contain at least non-negative elements. The result will be NA, if the vector contains negative elements.
prop	logical. Should the axes show proportions from 0 - 1 (default = TRUE), or percentages 0 - 100?
rescale	logical. Should the plot be rescaled so that 'c/n' is moved to the end of the x-axis and the plot is stretched out accordingly?

Value

returns a Lorenz curve plot (generated by ggplot2)

Examples

# Plot a Lorenz curve of a non-sparse data situation:
# 10 units of analysis and 100 events
crimes <- c(22,18,17,12,11,8,6,3,2,1)
lorenz(crimes)
# Because sum(crimes) > length(crimes), it is the normal Lorenz curve.

# Plot a Lorenz curve of a sparse data situation:
# 10 units of analysis and 5 events
crimes <- c(3,1,1,rep(0,7))
lorenz(crimes)

# You can rescale the plot so that 'c/n' is moved to the end of the x-axis
# (and the graph is stretched to the right accordingly)
lorenz(crimes, rescale = TRUE)

# Rescaling the graph is easier with very sparse data situation, as the
# adjusted line of maximal equality can become almost vertical from origin:
crimes <- c(3,1,1,rep(0,150))
lorenz(crimes)

wsteenbeek/lorenzgini documentation built on Oct. 11, 2020, 6:56 p.m.