Inequality Measures
computes the inequality within a vector according to the specified inequality measure
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)x |
a vector containing at least non-negative elements |
parameter |
parameter of the inequality measure (if set to |
type |
character string giving the measure used to compute inequality. must be one of the strings in the default argument (the first character is sufficient). defaults to "Gini". |
corr |
logical. Argument of the function |
square |
logical. Argument of the function |
na.rm |
logical. Should missing values ( |
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.
the value of the inequality measure
F A Cowell: Measurement of Inequality, 2000, in A B Atkinson / F Bourguignon (Eds): Handbook of Income Distribution, Amsterdam,
F A Cowell: Measuring Inequality, 1995 Prentice Hall/Harvester Wheatshef,
Marshall / Olkin: Inequalities: Theory of Majorization and Its Applications, New York 1979 (Academic Press).
# 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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