Nothing
## Analyzing results
## Computing distances
MUD <- PUD <- matrix(NA, nrow = Draws, ncol = SS)
for(i in 1:SS){
MUD[, i] <- (UMEU - MU[, i]) / abs(UMEU)
PUD[, i] <- (UMEU - PU[, i]) / abs(UMEU)
}
## Graph
PuDMean <- apply(PUD, 2, function(x) mean(x))
MuDMean <- apply(MUD, 2, function(x) mean(x))
PuDMin <- apply(PUD, 2, function(x) min(x))
MuDMin <- apply(MUD, 2, function(x) min(x))
PuDMax <- apply(PUD, 2, function(x) max(x))
MuDMax <- apply(MUD, 2, function(x) max(x))
ylims <- range(na.omit(c(PuDMax, MuDMax, PuDMin, MuDMin)))
plot(cbind(1:SS, PuDMean), type = "p", col = "blue", pch = 17, cex = 1.2,
ylim = ylims, ylab = "Relative deviations from 'true' utility",
xlab = "Sample Sizes", axes = FALSE)
points(1:SS, PuDMax, type = "p", col = "blue", cex = 1.2, pch = 22)
points(1:SS, PuDMin, type = "p", col = "blue", cex = 1.2, pch = 22)
points(1:SS, MuDMean, type = "p", col = "darkred", cex = 1.2, pch = 19)
points(1:SS, MuDMax, type = "p", col = "darkred", cex = 1.2, pch = 22)
points(1:SS, MuDMin, type = "p", col = "darkred", cex = 1.2, pch = 22)
arrows(x0 = 1:SS, y0 = PuDMin, y1 = PuDMax, code = 3, col = "blue",
length = 0.0, angle = 90, lwd = 2)
arrows(x0 = 1:SS, y0 = MuDMin, y1 = MuDMax, code = 3, col = "darkred",
length = 0.0, angle = 90, lwd = 1.0)
axis(1, at = 1:SS, Samples)
axis(2, pretty(ylims), pretty(ylims), las = 2)
box()
legend("topright", legend = c("PU mean deviation",
"PU min/max deviation",
"MU mean deviation",
"MU min/max deviation"),
pch = c(17, 22, 19, 22),
col = c(rep("blue", 2), rep("darkred", 2)))
abline(h = 0, col = "gray")
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