LDA visualization (individual and/or variable factor map(s)) for a PLNPCAfit object

LDA visualization (individual and/or variable factor map(s)) for a PLNPCAfit object

# S3 method for PLNLDAfit
plot(
  x,
  map = c("both", "individual", "variable"),
  nb_axes = min(3, x$rank),
  axes = seq.int(min(2, x$rank)),
  var_cols = "var_colors",
  plot = TRUE,
  main = NULL,
  ...
)

Arguments

x: an R6 object with class PLNPCAfit
map: the type of output for the PCA visualization: either "individual", "variable" or "both". Default is "both".
nb_axes: scalar: the number of axes to be considered when map = "both". The default is min(3,rank).
axes: numeric, the axes to use for the plot when map = "individual" or "variable". Default it c(1,min(rank))
var_cols: a character or factor to define the color associated with the variables. By default, all variables receive the default color of the current palette.
plot: logical. Should the plot be displayed or sent back as ggplot2 object
main: character. A title for the single plot (individual or variable factor map). If NULL (the default), an hopefully appropriate title will be used.
...: Not used (S3 compatibility).

Value

displays an individual and/or variable factor maps for the corresponding axes, and/or sends back a ggplot2 or gtable object

Examples

data(trichoptera)
trichoptera <- prepare_data(trichoptera$Abundance, trichoptera$Covariate)
myPLNLDA <- PLNLDA(Abundance ~ 1, grouping = Group, data = trichoptera)
#> 
#>  Performing discriminant Analysis...
#>  DONE!
if (FALSE) {
plot(myPLNLDA, map = "individual", nb_axes = 2)
}