contour-methods: Methods for Contour Plots in Package 'copula'

contour-methodsR Documentation

Methods for Contour Plots in Package 'copula'


Methods for function contour to draw contour lines aka a level plot for objects from package copula.


## S4 method for signature 'Copula'
contour(x, FUN,
                   n.grid = 26, delta = 0,
                   xlab = quote(u[1]), ylab = quote(u[2]),
                   box01 = TRUE, ...)
## S4 method for signature 'mvdc'
contour(x, FUN, xlim, ylim, n.grid = 26,
                   xlab = quote(x[1]), ylab = quote(x[2]),
		   box01 = FALSE, ...)



a "Copula" or a "mvdc" object.


the function to be plotted; typically dCopula or pCopula.


the number of grid points used in each dimension. This can be a vector of length two, giving the number of grid points used in x- and y-direction, respectively; the function FUN will be evaluated on the corresponding (x,y)-grid.


a small number in [0, 1/2) influencing the evaluation boundaries. The x- and y- vectors will have the range [0+delta, 1-delta], the default being [0,1].

xlab, ylab

the x-axis and y-axis labels.

xlim, ylim

the range of the x and y variables, respectively.


a logical specifying if a faint rectangle should be drawn on the boundary of [0,1]^2 (often useful for copulas, but typically not for general multivariate distributions ("mvdc")).


further arguments for (the default method of) contour(), e.g., nlevels, levels, etc.


Contour lines are drawn for "Copula" or "mvdc" objects, see x in the Arguments section.

See Also

The persp-methods for “perspective” aka “3D” plots.


contour(frankCopula(-0.8), dCopula)
contour(frankCopula(-0.8), dCopula, delta=1e-6)
contour(frankCopula(-1.2), pCopula)
contour(claytonCopula(2), pCopula)

## the Gumbel copula density is "extreme"
## --> use fine grid (and enough levels):
r <- contour(gumbelCopula(3), dCopula, n=200, nlevels=100)
range(r$z)# [0, 125.912]
## Now superimpose contours of three resolutions:
contour(r, levels = seq(1, max(r$z), by=2), lwd=1.5)
contour(r, levels = (1:13)/2, add=TRUE, col=adjustcolor(1,3/4), lty=2)
contour(r, levels = (1:13)/4, add=TRUE, col=adjustcolor(2,1/2),
        lty=3, lwd=3/4)

x <- mvdc(gumbelCopula(3), c("norm", "norm"),
          list(list(mean = 0, sd =1), list(mean = 1)))
contour(x, dMvdc, xlim=c(-2, 2), ylim=c(-1, 3))
contour(x, pMvdc, xlim=c(-2, 2), ylim=c(-1, 3))

copula documentation built on June 15, 2022, 5:07 p.m.