This function applied collapsed Gibbs sampling assuming that the number of mixture components is known.
collapsedGibbsBinMix(alpha, beta, gamma, K, m, burn,
data, thinning, z.true, outputDir)First shape parameter of the Beta prior distribution (strictly positive). Defaults to 1.
Second shape parameter of the Beta prior distribution (strictly positive). Defaults to 1.
K-dimensional vector (positive) corresponding to the parameters of the Dirichlet prior of the mixture weights. Default value: rep(1,K).
Number of clusters.
Number of MCMC iterations.
The number of initial MCMC iterations that will be discarded as burn-in period.
Binary data array.
Integer that defines a thinning of the reported MCMC sample. Under the default setting, every 5th MCMC iteration is saved.
An optional vector of cluster assignments considered as the ground-truth clustering of the observations. Useful for simulations.
The name of the produced output folder.