simulate_data: Simulate normal data for kmeans tests

In tanaylab/tglkmeans: Efficient Implementation of K-Means++ Algorithm

Simulate normal data for kmeans tests

Description

Creates nclust clusters normally distributed around 1:nclust

Usage

simulate_data(
  n = 100,
  sd = 0.3,
  nclust = 30,
  dims = 2,
  frac_na = NULL,
  add_true_clust = TRUE,
  id_column = TRUE
)

Arguments

n	number of observations per cluster
sd	sd
nclust	number of clusters
dims	number of dimensions
frac_na	fraction of NA in the first dimension
add_true_clust	add a column with the true cluster ids
id_column	add a column with the id

Value

simulated data

Examples

simulate_data(n = 100, sd = 0.3, nclust = 5, dims = 2)

# add 20% missing data
simulate_data(n = 100, sd = 0.3, nclust = 5, dims = 2, frac_na = 0.2)

tanaylab/tglkmeans documentation built on Jan. 27, 2024, 8:37 a.m.