mvnmix: Estimate mixture latent variable model

Description Usage Arguments Value Author(s) See Also Examples

Description

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

Usage

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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

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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"))


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