rvinecopulib (version 0.2.6.1.1)

plot.vinecop_dist: Plotting vinecop_dist and vinecop objects.

Description

There are two plotting generics for vinecop_dist objects. plot.vinecop_dist plots one or all trees of a given R-vine copula model. Edges can be labeled with information about the corresponding pair-copula. contour.vinecop_dist produces a matrix of contour plots (using plot.bicop).

Usage

# S3 method for vinecop_dist
plot(x, tree = 1, var_names = "ignore",
  edge_labels = NULL, ...)
# S3 method for vinecop
plot(x, tree = 1, var_names = "ignore",
  edge_labels = NULL, ...)
# S3 method for vinecop_dist
contour(x, tree = "ALL", cex.nums = 1, ...)
# S3 method for vinecop
contour(x, tree = "ALL", cex.nums = 1, ...)

Arguments

x

vinecop_dist object.

tree

"ALL" or integer vector; specifies which trees are plotted.

var_names

integer; specifies how to make use of variable names: "ignore" = variable names are ignored, "use" = variable names are used to annotate vertices, "legend" = uses numbers in plot and adds a legend for variable names.

edge_labels

character; either a vector of edge labels or one of the following: "family" = pair-copula family (see bicop_dist), "tau" = pair-copula Kendall's tau "family_tau" = pair-copula family and Kendall's tau, "pair" = for the name of the involved variables.

…

Unused for plot and passed to contour.bicop for contour.

cex.nums

numeric; expansion factor for font of the numbers.

Details

If you want the contour boxes to be perfect squares, the plot height should be 1.25/length(tree)*(d - min(tree)) times the plot width.

See Also

vinecop_dist, plot.bicop

Examples

# NOT RUN {
# set up vine copula model
d <- 20
n <- 2e2
u <- matrix(runif(n*d), n, d)
vc <- vinecop(u, "indep")

# plot
plot(vc, tree = c(1,2))
plot(vc, edge_labels = "pair")

# set up another vine copula model
pcs <- lapply(1:3, function(j) # pair-copulas in tree j
    lapply(runif(4-j), function(cor) bicop_dist("gaussian", 0, cor)))
mat <- matrix(c(1, 2, 3, 4, 1, 2, 3, 0, 1, 2, 0, 0, 1, 0, 0, 0), 4, 4)
vc <- vinecop_dist(pcs, mat)

# contour plot
contour(vc)

# }