ineq(x, parameter = NULL, type = c("Gini", "RS", "Atkinson", "Theil", "Kolm", "var", "square.var", "entropy"), na.rm = TRUE)
Gini(x, corr = FALSE, na.rm = TRUE)
RS(x, na.rm = TRUE)
Atkinson(x, parameter = 0.5, na.rm = TRUE)
Theil(x, parameter = 0, na.rm = TRUE)
Kolm(x, parameter = 1, na.rm = TRUE)
var.coeff(x, square = FALSE, na.rm = TRUE)
entropy(x, parameter = 0.5, na.rm = TRUE)NULL
the default parameter of the respective measure is used)Gini specifying whether
or not a finite sample correction should be applied.var.coeff, for details
see below.NAs) be removed
prior to computations? If set to FALSE the computations yield
NA.ineq is just a wrapper for the inequality measures Gini,
RS, Atkinson, Theil, Kolm,var.coeff,
entropy. If parameter is set to NULL the default from
the respective function is used. Gini is the Gini coefficient, RS is the the Ricci-Schutz
coefficient (also called Pietra's measure), Atkinson gives
Atkinson's measure and Kolm computes Kolm's measure.
If the parameter in Theil is 0 Theil's entropy measure is
computed, for every other value Theil's second measure is
computed.
ineq(x, type="var") and var.coeff(x) respectively
compute the coefficient of variation, while
ineq(x,type="square.var") and var.coeff(x, square=TRUE)
compute the squared coefficient of variation.
entropy computes the generalized entropy, which is for
parameter 1 equal to Theil's entropy coefficient and for parameter
0 equal to the second measure of Theil.
F A Cowell: Measuring Inequality, 1995 Prentice Hall/Harvester Wheatshef,
Marshall / Olkin: Inequalities: Theory of Majorization and Its Applications, New York 1979 (Academic Press).
conc, pov# generate vector (of incomes)
x <- c(541, 1463, 2445, 3438, 4437, 5401, 6392, 8304, 11904, 22261)
# compute Gini coefficient
ineq(x)
# compute Atkinson coefficient with parameter=0.5
ineq(x, parameter=0.5, type="Atkinson")
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