collapsedGibbsBinMix: collapsed Gibbs sampler

In BayesBinMix: Bayesian Estimation of Mixtures of Multivariate Bernoulli Distributions

Description

This function applied collapsed Gibbs sampling assuming that the number of mixture components is known.

Usage

collapsedGibbsBinMix(alpha, beta, gamma, K, m, burn, 
	data, thinning, z.true, outputDir)

Arguments

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

Note

Not really used.

Author(s)

Panagiotis Papastamoulis

BayesBinMix documentation built on May 2, 2019, 3:26 a.m.