copula (version 0.999-10)

contour-methods: Methods for Function 'contour' in Package 'copula'

Description

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

Usage

## S3 method for class 'copula':
contour(x, fun,
      n = 51, delta = 0, box01 = TRUE, \dots)
## S3 method for class 'mvdc':
contour(x, fun,
      xlim, ylim, nx = 51, ny = 51,
      xis = seq(xlim[1], xlim[2], length = nx),
      yis = seq(ylim[1], ylim[2], length = ny),
      box01 = TRUE, ...)

Arguments

x

either a "copula" or a "mvdc" object.

fun

the function to be plotted; typically dCopula or pCopula.

n

(for "copula":) the number of points in both directions to do the plotting. The function fun will be evaluated on a grid of size $n \times n$.

delta

a very small number in $[0, \frac 1 2)$, defaulting to zero. The x- and y-ranges to be used for plotting will be [0+delta, 1-delta], i.e., [0,1] by default.

xlim, ylim

("mvdc":) the range of the x or y variable, respectively.

nx,ny

("mvdc":) the number of points in x- or y-direction, respectively. The function fun will be evaluated on a grid of size $nx \times ny$.

xis, yis

("mvdc":) instead of specifying xlim, ylim and nx, ny, the numeric vectors (of length nx and ny) may be specified directly.

box01

logical specifying if faint rectangle should be drawn at the $[0,1]^2$ borders.

...

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

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))