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.NA
s) 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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