discr.sims.fat_tails: Discriminability Spread Simulation

In JINJINT/aLDG: Compute and evaluate the bivariate dependence

Discriminability Spread Simulation

Description

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

Usage

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

Arguments

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.

Author(s)

Eric Bridgeford

Examples

library(mgc)
sim <- discr.sims.fat_tails(100, 3, 2)

JINJINT/aLDG documentation built on April 1, 2022, 6:23 p.m.