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Monotonize a step function by rearrangement
rearrange(f,xmin,xmax)
object of class stepfun
minimum of the support of the rearranged f
maximum of the support of the rearranged f
Produces transformed stepfunction that is monotonic increasing.
Given a stepfunction
Chernozhukov, V., I. Fernandez-Val, and A. Galichon, (2006) Quantile and Probability Curves without Crossing, Econometrica, forthcoming.
Chernozhukov, V., I. Fernandez-Val, and A. Galichon, (2009) Improving Estimates of Monotone Functions by Rearrangement, Biometrika, 96, 559--575.
Hardy, G.H., J.E. Littlewood, and G. Polya (1934) Inequalities, Cambridge U. Press.
# NOT RUN {
data(engel)
z <- rq(foodexp ~ income, tau = -1,data =engel)
zp <- predict(z,newdata=list(income=quantile(engel$income,.03)),stepfun = TRUE)
plot(zp,do.points = FALSE, xlab = expression(tau),
ylab = expression(Q ( tau )), main="Engel Food Expenditure Quantiles")
plot(rearrange(zp),do.points = FALSE, add=TRUE,col.h="red",col.v="red")
legend(.6,300,c("Before Rearrangement","After Rearrangement"),lty=1,col=c("black","red"))
# }
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