persp-methods {copula} | R Documentation |
Methods for function persp
to draw perspective plots (of
two dimensional distributions from package copula).
## S4 method for signature 'Copula' persp(x, FUN, n.grid = 26, delta = 0, xlab = "u1", ylab = "u2", zlab = deparse(substitute(FUN))[1], theta = -30, phi = 30, expand = 0.618, ticktype = "detail", ...) ## S4 method for signature 'mvdc' persp(x, FUN, xlim, ylim, n.grid = 26, xlab = "x1", ylab = "x2", zlab = deparse(substitute(FUN))[1], theta = -30, phi = 30, expand = 0.618, ticktype = "detail", ...)
x |
|
FUN |
|
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 |
delta |
A small number in [0, 1/2)
influencing the evaluation boundaries. The x- and y- vectors will
have the range |
xlim, ylim |
The |
xlab, ylab, zlab, theta, phi, expand, ticktype, ... |
Arguments
for (the default method of) |
invisible
; a list with the following components:
x, y |
The numeric vectors, as passed to |
z |
The matrix of evaluated |
persp |
the 4 x 4 transformation matrix
returned by |
Perspective plots for both "copula"
or
"mvdc"
objects, see x
in the
Arguments section.
The contour-methods
for drawing contour lines of the
same functions.
persp(frankCopula(-0.8), dCopula) persp(claytonCopula(2), pCopula, main = "CDF of claytonCopula(2)") ## An example with negative tau: (th1 <- iTau(amhCopula(), -0.1)) persp(amhCopula(th1), dCopula) persp(amhCopula(th1), pCopula, ticktype = "simple") # no axis ticks mvNN <- mvdc(gumbelCopula(3), c("norm", "norm"), list(list(mean = 0, sd = 1), list(mean = 1))) persp(mvNN, dMvdc, xlim=c(-2, 2), ylim=c(-1, 3), main = "Density") persp(mvNN, pMvdc, xlim=c(-2, 2), ylim=c(-1, 3), main = "Cumulative Distr.")