plot.permutation: Plot a fitted rgcca permutation object

In Tenenhaus/RGCCA: Regularized (or Sparse) Generalized Canonical Correlation Analysis (R/SGCCA) for multi-block data analysis

Plot a fitted rgcca permutation object

Description

Plot a fitted rgcca permutation object. The various set of tuning parameters are represented on the y-axis and the RGCCA objective function - obtained from both the orginal and permuted blocks - on the x-axis. If type = "zstat" the value of the zstat for the various parameter sets are reported on the x-axis.

Usage

## S3 method for class 'permutation'
plot(
  x,
  type = "crit",
  cex = 1,
  title = NULL,
  cex_main = 14 * cex,
  cex_sub = 12 * cex,
  cex_point = 3 * cex,
  cex_lab = 12 * cex,
  display_order = TRUE,
  show_legend = FALSE,
  ...
)

Arguments

x	A fitted rgcca_permutation object (see rgcca_permutation).
type	A character string indicating which criterion to plot. Default is 'crit' for the RGCCA criterion. Otherwise, the pseudo Z-score is used.
cex	A numeric defining the size of the objects in the plot. Default is one.
title	A character string giving the title of the plot.
cex_main	A numeric defining the font size of the title. Default is 14 * cex.
cex_sub	A numeric defining the font size of the subtitle. Default is 12 * cex.
cex_point	A numeric defining the font size of the points. Default is 3 * cex.
cex_lab	A numeric defining the font size of the labels. Default is 12 * cex.
display_order	A logical value for ordering the variables. If TRUE, variables are ordered from highest to lowest absolute value. If FALSE, the block order is used. Default is TRUE.
show_legend	A boolean indicating if legend should be shown (default is FALSE).
...	Additional graphical parameters.

Value

A ggplot2 plot object.

Examples

data(Russett)
A <- list(
  agriculture = Russett[, seq(3)],
  industry = Russett[, 4:5],
  politic = Russett[, 6:11]
)

perm.out <- rgcca_permutation(A, par_type = "tau", n_perms = 2, n_cores = 1)
print(perm.out)
plot(perm.out)

perm.out <- rgcca_permutation(A,
  par_type = "sparsity",
  n_perms = 5, n_cores = 1
)
print(perm.out)
plot(perm.out, type = "zstat")

Tenenhaus/RGCCA documentation built on March 16, 2023, 2:04 p.m.