fabMix (version 5.1)

update_z4_Sj: Collapsed Gibbs for \(z\)

Description

Collapsed Gibbs for \(z\)

Usage

update_z4_Sj(w, mu, Lambda, SigmaINV, K, x_data)

Value

Allocation vector

Arguments

w

vector with length \(K\) consisting of mixture weights

mu

\(K\times p\) array containing the marginal means

Lambda

\(K\times p\) array with factor loadings

SigmaINV

\(K\times p\times p\) array containing the precision matrix per component

K

Number of components

x_data

\(n\times p\) matrix containing the observed data

Author

Panagiotis Papastamoulis

Examples

library('fabMix')
# simulate some data
n = 8                # sample size
p = 5                # number of variables
q = 2                # number of factors
K = 2                # true number of clusters
sINV_diag = 1/((1:p))    # diagonal of inverse variance of errors
set.seed(100)
syntheticDataset <- simData(sameLambda=TRUE,K.true = K, n = n, q = q, p = p, 
                        sINV_values = sINV_diag)
SigmaINV <- array(data = 0, dim = c(K,p,p))
for(k in 1:K){
	diag(SigmaINV[k,,]) <- 1/diag(syntheticDataset$variance) + rgamma(p, shape=1, rate = 1)
}

# use the real values as input and simulate allocations
update_z4_Sj(w = syntheticDataset$weights, mu = syntheticDataset$means, 
	Lambda = syntheticDataset$factorLoadings, 
	SigmaINV = SigmaINV, 
	K = K, x_data = syntheticDataset$data)$z