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

In copula: Multivariate Dependence with Copulas

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 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, ...)

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

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 Sept. 11, 2024, 7:48 p.m.