Perspective Plots - 'wireframe2' in Package 'copula'
## S4 method for signature 'matrix' wireframe2(x, xlim = range(x[,1], finite = TRUE), ylim = range(x[,2], finite = TRUE), zlim = range(x[,3], finite = TRUE), xlab = NULL, ylab = NULL, zlab = NULL, alpha.regions = 0.5, scales = list(arrows = FALSE, col = "black"), par.settings = standard.theme(color = FALSE), draw.4.pCoplines = FALSE, ...) ## _identical_ method for 'data.frame' as for 'matrix' ## S4 method for signature 'Copula' wireframe2(x, FUN, n.grid = 26, delta = 0, xlim = 0:1, ylim = 0:1, zlim = NULL, xlab = quote(u[1]), ylab = quote(u[2]), zlab = list(deparse(substitute(FUN))[1], rot = 90), draw.4.pCoplines = identical(FUN, pCopula), ...) ## S4 method for signature 'mvdc' wireframe2(x, FUN, n.grid = 26, xlim, ylim, zlim = NULL, xlab = quote(x[1]), ylab = quote(x[2]), zlab = list(deparse(substitute(FUN))[1], rot = 90), ...)
x |
a |
xlim, ylim, zlim |
the x-, y- and z-axis limits. |
xlab, ylab, zlab |
the x-, y- and z-axis labels. |
alpha.regions |
see |
scales |
|
par.settings |
See |
FUN |
the |
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 |
draw.4.pCoplines |
logical indicating if the 4 known border
segments of a copula distribution function, i.e., |
... |
additional arguments passed to the underlying |
An object of class “trellis” as returned by wireframe()
.
Wireframe plots for objects of class "matrix"
,
"data.frame"
, "Copula"
or
"mvdc"
.
The persp-methods
for drawing perspective plots via base graphics.
The lattice-based contourplot2-methods
.
## For 'matrix' objects ## The Frechet--Hoeffding bounds W and M n.grid <- 26 u <- seq(0, 1, length.out = n.grid) grid <- expand.grid("u[1]" = u, "u[2]" = u) W <- function(u) pmax(0, rowSums(u)-1) # lower bound W M <- function(u) apply(u, 1, min) # upper bound M x.W <- cbind(grid, "W(u[1],u[2])" = W(grid)) # evaluate W on 'grid' x.M <- cbind(grid, "M(u[1],u[2])" = M(grid)) # evaluate M on 'grid' wireframe2(x.W) wireframe2(x.W, shade = TRUE) # plot of W wireframe2(x.M, drape = TRUE) # plot of M ## For 'Copula' objects cop <- frankCopula(-4) wireframe2(cop, pCopula) # the copula wireframe2(cop, pCopula, shade = TRUE) # ditto, "shaded" wireframe2(cop, pCopula, shade = TRUE, col = "gray60") # ditto, "shaded"+grid wireframe2(cop, pCopula, drape = TRUE, xlab = quote(x[1])) # adjusting an axis label wireframe2(cop, dCopula, delta=0.01) # the density wireframe2(cop, dCopula) # => the density is set to 0 on the margins wireframe2(cop, function(u, copula) dCopula(u, copula, log=TRUE), zlab = list(quote(log(c(u[1],u[2]))), rot=90), main = "dCopula(.., log=TRUE)") ## For 'mvdc' objects mvNN <- mvdc(gumbelCopula(3), c("norm", "norm"), list(list(mean = 0, sd = 1), list(mean = 1))) wireframe2(mvNN, dMvdc, xlim=c(-2, 2), ylim=c(-1, 3))
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