Lc.plot {ineq} | R Documentation |
plots the Lorenz curve of a vector x (like computed by Lc
)
Lc.plot(Lc, general=F, lwd=2,xlab="p",ylab="L(p)",main="Lorenz curve", new=F, col=1, lty=1)
Lc |
a list like provided by Lc |
general |
logical flag. if TRUE the generalized Lorenz curve will be plotted |
new |
logical flag. if TRUE the curve will be plotted into an existing plot. |
... |
graphical parameters |
Achim Zeileis zeileis@ci.tuwien.ac.at
B C Arnold: Majorization and the Lorenz Order: A Brief Introduction, 1987, Springer,
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.
# income distribution of the USA in 1968 (in 10 classes) # x vector of class means, n vector of class frequencies x <- c(541, 1463, 2445, 3438, 4437, 5401, 6392, 8304, 11904, 22261) n <- c(482, 825, 722, 690, 661, 760, 745, 2140, 1911, 1024) # compute minimal Lorenz curve (= no inequality in each group) Lc.min <- Lc(x, n=n) # compute maximal Lorenz curve (limits of Mehran) Lc.max <- Lc.mehran(x,n) # plot both Lorenz curves in one plot Lc.plot(Lc.min) Lc.plot(Lc.max, new=T, col=4) # add the theoretic Lorenz curve of a Lognormal-distribution with (var=0.78) theor.Lc.plot(type="lognorm", parameter=0.78) # add the theoretic Lorenz curve of a Dagum-distribution theor.Lc.plot(type="Dagum", parameter=c(3.4,2.6))