discr.sims.fat_tails: Discriminability Spread Simulation
In mgc: Multiscale Graph Correlation

A function to simulate data with the same mean that spreads as class id increases.

discr.sims.fat_tails(
  n,
  d,
  K,
  signal.scale = 1,
  rotate = FALSE,
  class.equal = TRUE,
  ind = FALSE
)

`n`	the number of samples.
`d`	the number of dimensions.
`K`	the number of classes in the dataset.
`signal.scale`	the scaling for the signal dimension. Defaults to `1`.
`rotate`	whether to apply a random rotation. Defaults to `TRUE`.
`class.equal`	whether the number of samples/class should be equal, with each class having a prior of 1/K, or inequal, in which each class obtains a prior of k/sum(K) for k=1:K. Defaults to `TRUE`.
`ind`	whether to sample x and y independently. Defaults to `FALSE`.