gau_clust_diff {cardinalR}

Generate Gaussian Clusters with Different Points

Description

This function generates Gaussian clusters with different numbers of points per cluster.

Usage

gau_clust_diff(
  clust_size_vec,
  num_clust,
  mean_matrix,
  var_vec,
  num_dims,
  num_noise,
  min_n,
  max_n
)

Arguments

clust_size_vec

A vector specifying the number of points in each cluster.

num_clust

The number of clusters to generate.

mean_matrix

A matrix where each row represents the mean vector for a cluster.

var_vec

A vector specifying the variance for each cluster.

num_dims

The number of effective dimensions for the data points.

num_noise

The number of additional noise dimensions to be generated.

min_n

The minimum value for the noise added to the data points.

max_n

The maximum value for the noise added to the data points.

Value

A matrix containing the generated Gaussian clusters with different points.

Examples

# Generate Gaussian clusters with custom parameters
set.seed(20240412)
data <- gau_clust_diff(
  clust_size_vec = c(50, 100, 200, 50),
  num_clust = 4, mean_matrix =
    rbind(
      c(1, 0, 0, 0, 0, 0), c(0, 1, 0, 0, 0, 0),
      c(0, 0, 1, 0, 0, 0), c(0, 0, 0, 1, 0, 0)
    ),
  var_vec = c(0.02, 0.05, 0.06, 0.1),
  num_dims = 6, num_noise = 4,
  min_n = -0.05, max_n = 0.05
)