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REAT (version 3.0.2)

disp: Concentration/inequality/dispersion measures

Description

Calculating a set of concentration/inequality/dispersion measures

Usage

disp(x, weighting = NULL, at.epsilon = 0.5, na.rm = TRUE)

Arguments

x

a numeric vector or matrix or columns from a data frame

weighting

a weighting vector, e.g. population

at.epsilon

Weighting parameter \(\epsilon\) for the Atkinson index

na.rm

logical argument that indicates whether NA values should be excluded before computing results

Value

A matrix containing the concentration/inequality measures.

Details

This function is a convenient wrapper for all functions calculating concentration/inequality measures.

References

Gluschenko, K. (2018): “Measuring regional inequality: to weight or not to weight?” In: Spatial Economic Analysis, 13, 1, p. 36-59.

Portnov, B.A./Felsenstein, D. (2010): “On the suitability of income inequality measures for regional analysis: Some evidence from simulation analysis and bootstrapping tests”. In: Socio-Economic Planning Sciences, 44, 4, p. 212-219.

See Also

atkinson, coulter, dalton, cv, gini2, herf, hoover, sd2, theil, williamson

Examples

Run this code
# NOT RUN {
data(Automotive)

disp(Automotive$Turnover2008)
disp(Automotive[4:8])
# }

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