Description Usage Arguments Details Author(s)
This function implements full Gibbs sampling to simulate an MCMC sample from the posterior distribution assuming known number of mixture components.
1 2 | gibbsBinMix(alpha, beta, gamma, K, m, burn, data,
thinning, z.true, outputDir)
|
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 |
Number of clusters. |
m |
Number of MCMC iterations. |
burn |
Burn-in period. |
data |
Binary data. |
thinning |
Thinning of the simulated chain. |
z.true |
An optional vector of cluster assignments considered as the ground-truth clustering of the observations. Useful for simulations. |
outputDir |
Output directory. |
Not really used.
Panagiotis Papastamoulis
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