R: Estimate mixture latent variable model

mvnmix {lava} | R Documentation

## Estimate mixture latent variable model

### Description

Estimate mixture latent variable model

### 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

### Details

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

### Value

A `mixture` object

### Author(s)

Klaus K. Holst

### See Also

`mixture`

### Examples

    data(faithful)
    set.seed(1)
    M1 <- mvnmix(faithful[,"waiting",drop=FALSE],k=2)
    M2 <- mvnmix(faithful,k=2)
    if (interactive()) {
        par(mfrow=c(2,1))
        plot(M1,col=c("orange","blue"),ylim=c(0,0.05))
        plot(M2,col=c("orange","blue"))
    }

[Package lava version 1.6.1 Index]