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ROCscore <- function(xobs, yobs, type = "output") {
# verification
n1 <- nrow(xobs) # number of observations
p.input <- ncol(xobs) # number of inputs
# verification of some conditions
if(n1 != nrow(yobs))
stop("xobs and yobs have not the same number of observations")
match.arg(type,c("output","input","hyper"))
# initialisation
alpha <- seq(0.01, 1, by = 0.01)
m <- c(1, 5, 8, 11, 14, 17, 20, 23, 26, 29, 32, 35, 40, 45,
50, 55, 60, 65, 70, 75, 80, 85, 90, 95,
seq(100, 2500, length.out = 76))
# Representation of the alpha quantile efficiency frontier
oldpar <- par(no.readonly = TRUE)
on.exit(par(oldpar))
# 1- Computation of the alpha-quantile score
perf1 <- numeric(length(alpha))
perf2 <- numeric(length(alpha))
for (k in 1:length(alpha)) {
res1 <- alphascore(xobs,yobs, alpha=alpha[k])[,type] # score computed on (xtab,ytab)
res2 <- ordermscore(xobs,yobs, m=m[k])[,type] # score computed on (xtab,ytab)
perf1[k] <- length(which(res1 > 1)) / n1
perf2[k] <- length(which(res2>1)) / n1
}
plot(alpha, perf1, type = 'l', xlab = "alpha",
ylab = "Percentage of super-efficiency firms",
ylim = c(0, 1),
col = 'royalblue')
par(new = TRUE)
plot(m, perf2, type = 'l', lty = 2, ann = FALSE, yaxt = "n", xaxt="n",
yaxt = "n", ylim = c(0, 1), col = 'red')
axis(3)
mtext(side = 3, "m")
legend("topright", legend = c("f(alpha)", "f(m)"),
lty = 1:2, col = c("royalblue", "red"))
res <- data.frame(alpha, perf1, m, perf2)
names(res) <- c("alpha", "f(alpha)", "m", "f(m)")
return(res)
}
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