mvnmix: Estimate mixture latent variable model

In lava.mixture: Mixtures of Linear Latent Variable Models

Description

Estimate parameters in a mixture of latent variable models via the EM algorithm.

Usage

mvnmix(data, k=2, theta, steps=500,
                 tol=1e-16, lambda=0,
                 mu=NULL,
                 silent=TRUE, extra=FALSE, ...
                 ) 

Arguments

data	data.frame
k	Number of mixture components
theta	Optional starting values
steps	Maximum number of iterations
tol	Convergence tolerance of EM algorithm
lambda	Added to diagonal of covariance matrix (to avoid singularities)
mu	Initial centres (if unspecified random centres will be chosen)
silent	Turn on/off output messages
extra	Extra debug information
...	Additional arguments parsed to lower-level functions

Value

A mixture object

Author(s)

Klaus K. Holst

See Also

mvnmix

Examples

data(faithful)
set.seed(1)
M1 <- mvnmix(faithful[,"waiting",drop=FALSE],k=2)
M2 <- mvnmix(faithful,k=2)

par(mfrow=c(2,1))
plot(M1,col=c("orange","blue"),ylim=c(0,0.05))
plot(M2,col=c("orange","blue"))

lava.mixture documentation built on May 2, 2019, 6:10 p.m.