plot.vinecop_dist {rvinecopulib}

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 class 'vinecop_dist'
plot(x, tree = 1, var_names = "ignore", edge_labels = NULL, ...)

## S3 method for class 'vinecop'
plot(x, tree = 1, var_names = "ignore", edge_labels = NULL, ...)

## S3 method for class 'vinecop_dist'
contour(x, tree = "ALL", cex.nums = 1, ...)

## S3 method for class '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,

• '"hide"“ = no numbers or names, just the node.

edge_labels

character; options are:

• "family" = pair-copula family (see ⁠[bicop_dist()]⁠),

• ‘"tau"“ = pair-copula Kendall’s tau

• ‘"family_tau"“ = pair-copula family and Kendall’s tau,

• '"pair"“ = 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.

The plot() method returns an object that (among other things) contains the igraph representation of the graph; see Examples.

Author(s)

Thomas Nagler, Thibault Vatter

See Also

vinecop_dist, plot.bicop

Examples

# set up vine copula model
u <- matrix(runif(20 * 10), 20, 10)
vc <- vinecop(u, family = "indep")

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

# extract igraph representation
plt <- plot(vc, edge_labels = "family_tau")
igr_obj <- get("g", plt$plot_env)[[1]]
igr_obj  # print object
igraph::E(igr_obj)$name  # extract edge labels

# 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 <- rvine_matrix_sim(4)
vc <- vinecop_dist(pcs, mat)

# contour plot
contour(vc)