Learn R Programming

fdm2id (version 0.9.6)

data.gauss: Gaussian mixture dataset

Description

Generate a random multidimentional gaussian mixture.

Usage

data.gauss(
  n = 1000,
  k = 2,
  prob = rep(1/k, k),
  mu = cbind(rep(0, k), seq(from = 0, by = 3, length.out = k)),
  cov = rep(list(matrix(c(6, 0.9, 0.9, 0.3), ncol = 2, nrow = 2)), k),
  levels = NULL,
  graph = TRUE,
  seed = NULL
)

Value

A randomly generated dataset.

Arguments

n

Number of observations.

k

The number of classes.

prob

The a priori probability of each class.

mu

The means of the gaussian distributions.

cov

The covariance of the gaussian distributions.

levels

Name of each class.

graph

A logical indicating whether or not a graphic should be plotted.

seed

A specified seed for random number generation.

See Also

data.diag, data.parabol, data.target2, data.twomoons, data.xor

Examples

Run this code
data.gauss ()

Run the code above in your browser using DataLab