Plot the symmetric deviation function.

The symmetric deviation function is the probability for a given target in the objective space to belong to the symmetric difference between the Vorob'ev expectation and a realization of the (random) attained set.

Usage

symdevplot(
  x,
  sets,
  VE,
  threshold,
  nlevels = 11,
  ve.col = "blue",
  xlim = NULL,
  ylim = NULL,
  legend.pos = "topright",
  main = "Symmetric deviation function",
  col.fun = function(n) gray(seq(0, 0.9, length.out = n)^2)
)

Arguments

x: matrix()|data.frame()
Matrix or data frame of numerical values, where each row gives the coordinates of a point. If sets is missing, the last column of x gives the sets.
sets: integer()
A vector that indicates the set of each point in x. If missing, the last column of x is used instead.
VE, threshold: Vorob'ev expectation and threshold, e.g., as returned by moocore::vorobT().
nlevels: (integer(1))
Number of levels in which is divided the range of the symmetric deviation.
ve.col: Plotting parameters for the Vorob'ev expectation.
xlim, ylim, main: Graphical parameters, see plot.default().
legend.pos: The position of the legend, see legend(). A value of "none" hides the legend.
col.fun: Function that creates a vector of n colors, see heat.colors().

Value

No return value, called for side effects

References

BinGinRou2015gauparmoocore

C. Chevalier (2013), Fast uncertainty reduction strategies relying on Gaussian process models, University of Bern, PhD thesis.

Molchanov2005theorymoocore

Author

Mickael Binois

Examples

data(CPFs, package = "moocore")
res <- moocore::vorobT(CPFs, reference = c(2, 200))
print(res$threshold)
#> [1] 44.14062

## Display Vorob'ev expectation and attainment function
# First style
eafplot(CPFs[,1:2], sets = CPFs[,3], percentiles = c(0, 25, 50, 75, 100, res$threshold),
        main = substitute(paste("Empirical attainment function, ",beta,"* = ", a, "%"),
                          list(a = formatC(res$threshold, digits = 2, format = "f"))))


# Second style
eafplot(CPFs[,1:2], sets = CPFs[,3], percentiles = c(0, 20, 40, 60, 80, 100),
        col = gray(seq(0.8, 0.1, length.out = 6)^0.5), type = "area",
        legend.pos = "bottomleft", extra.points = res$VE, extra.col = "cyan",
        extra.legend = "VE", extra.lty = "solid", extra.pch = NA, extra.lwd = 2,
        main = substitute(paste("Empirical attainment function, ",beta,"* = ", a, "%"),
                          list(a = formatC(res$threshold, digits = 2, format = "f"))))

# Vorob'ev deviation
VD <- moocore::vorobDev(CPFs, reference = c(2, 200), VE = res$VE)
# Display the symmetric deviation function.
symdevplot(CPFs, VE = res$VE, threshold = res$threshold, nlevels = 11)

# Levels are adjusted automatically if too large.
symdevplot(CPFs, VE = res$VE, threshold = res$threshold, nlevels = 200, legend.pos = "none")


# Use a different palette.
symdevplot(CPFs, VE = res$VE, threshold = res$threshold, nlevels = 11, col.fun = heat.colors)