discr.sims.log: Discriminability Logarithmic Simulation

Description Usage Arguments Author(s) Examples

View source: R/simulations.R

Description

A function to simulate multi-class data with a logarithmic class-mean trend.

Usage

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discr.sims.log(n, d, K, sig.scale = 1, mean.scale = 1, base = 2,
  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.

sig.scale

the scaling for the class-variance. Defaults to 1.

mean.scale

the scaling for the class-means. Defaults to 1.

base

the base to use for the logarithm. Defaults to 2.

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

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

neurodata/mgc-r documentation built on Feb. 3, 2019, 12:43 a.m.