collapsedGibbsBinMix: collapsed Gibbs sampler

Description Usage Arguments Note Author(s)

Description

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

Usage

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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.