GaussianMixture: Simulate Gaussian Mixture Model with Normal-Wishart...
In thetianshuhuang/bmcc_r: Markov Chain Bayesian Clustering

Simulate Gaussian Mixture Model with Normal-Wishart components

1 2	GaussianMixture(n = 1000L, k = 3L, d = 2L, r = 1, alpha = 10, df = NULL, symmetric = FALSE, shuffle = TRUE)

`n`	Number of data points
`k`	Number of clusters
`d`	Number of dimensions
`r`	Balance parameter; the kth cluster has assignment probability ~ r^k
`alpha`	Concentration parameter; higher alpha will result in cluster means being farther apart
`df`	Degrees of freedom for Normal-Wishart. If NULL, uses df = d.
`symmetric`	If TRUE, uses N(0, I) instead of sampling from wishart.
`shuffle`	If TRUE, created points are in random order.