fabMix (version 5.1)

complete.log.likelihood_Sj: Complete log-likelihood function for xUx models.

Description

Complete log-likelihood function for models with different error variance per component (xUx).

Usage

complete.log.likelihood_Sj(x_data, w, mu, Lambda, SigmaINV, z)

Value

complete log-likelihood value

Arguments

x_data

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

w

a vector of length \(K\) containing the mixture weights

mu

\(K\times p\) matrix containing the marginal means per component

Lambda

\(K\times p\times q\) array of factor loadings per component (maybe restricted to be the same)

SigmaINV

\(K\times p\times p\) precision matrix (inverse covariance) per component

z

The allocation vector.

Author

Panagiotis Papastamoulis

Examples

	library('fabMix')
	data(waveDataset1500)
	x_data <- waveDataset1500[ 1:20, -1] # data
	z <-  waveDataset1500[ 1:20, 1]	# class
	p <- dim(x_data)[2]
	q <- 2
	K <- length(table(z))		# 3 classes
	# give some arbitrary values to the parameters:
	set.seed(1)
	w <- rep(1/K, K)
	mu <- array( runif(K * p), dim = c(K,p) )
	Lambda <- array( runif(K*p*q), dim = c(K,p,q) )
	SigmaINV <- array( c(0.5, 0.75, 1), dim = c(K,p,p))
	# compute the complete.log.likelihood
	complete.log.likelihood_Sj(x_data = x_data, w = w, mu = mu, 
		Lambda = Lambda, SigmaINV = SigmaINV, z = z)