copula (version 0.999-19)

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

Description

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

Usage

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

Arguments

x

a "'>Copula" or a "'>mvdc" object.

FUN

the function to be plotted; typically dCopula or pCopula.

n.grid

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.

delta

a small number in \([0, \frac 1 2)\) 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.

box01

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.

Methods

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.

Examples

# NOT RUN {
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))
# }

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