fabMix (version 5.1)

complete.log.likelihood: Complete log-likelihood function for xCx models.

Description

Complete log-likelihood function for models with same error variance per component (xCx).

Usage

complete.log.likelihood(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

SigmaINV

\(p\times p\) precision matrix (inverse covariance)

z

A vector of length \(n\) containing the allocations of the \(n\) datapoints to the \(K\) mixture components

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(1, dim = c(p,p))
	# compute the complete.log.likelihood
	complete.log.likelihood(x_data = x_data, w = w, mu = mu, 
		Lambda = Lambda, SigmaINV = SigmaINV, z = z)