Generate Cluster and Curvilinear Data with Noise

This function generates data with two clusters, one following a curvilinear pattern and the other distributed randomly.

Usage

gau_curvy_clust(n, clust_size_vec, num_noise, min_n, max_n)

Arguments

n

The total number of data points to be generated.

clust_size_vec

A vector specifying the number of points for each cluster. If not provided, the n is divided equally between the two clusters.

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 data, with each row representing a data point.

Examples

# Generate cluster and curvilinear data with custom parameters
set.seed(20240412)
data <- gau_curvy_clust(
  n = 300, clust_size_vec = c(100, 200), num_noise = 3,
  min_n = -0.05, max_n = 0.05
)