simMultGauss: Simulate MVN clusters with outliers Simulate data points from...

In AmIACommonGuy/RobustEM: Robust Expectation Maximization Algorithm against Outliers

Simulate MVN clusters with outliers Simulate data points from several different gaussian distributions. The number of points from different distributions are the same.

Description

Simulate MVN clusters with outliers

Simulate data points from several different gaussian distributions. The number of points from different distributions are the same.

Usage

simMultGauss(n, d, cluster, out_perc, out_mag, cov_scale = 1)

Arguments

n	Number of points in each Gaussian distribution
d	Dimension of each point
cluster	Number of clusters
out_perc	Proportion of outliers in each cluster
out_mag	Magitude of covariance difference between outliers and non-outliers
cov_scale	Covariance Scaling constant for the covariance of non-outliers

Value

A list with:

All the means of each cluster in a c*d matrix

All the covariances of each cluster in a list of matrices(length c, each matrix d*d)

All the simulated data points(n*c rows, d columns)

All the simulated outliers

Examples

sim_info <- simMultGauss(n = 120, d = 2, cluster = 6, out_perc = 0.03, out_mag = 4)

AmIACommonGuy/RobustEM documentation built on April 24, 2022, 5:38 a.m.