choose.nmixt {varmixt} | R Documentation

## Fow to choose the number of components in the mixture model

### Description

This function finds the number of components that minimizes the BIC criteria.

### Usage

    choose.nmixt(VAR,df,crit=c("AIC","BIC")[2],stop.crit=stop.crit.2,display=TRUE,
                           criterion=c("likelihood","parameter")[1])

### Arguments

`VAR` | Vector of estimated variance
`df` | degrees of freedom of the estimated variance
`crit` | method for choosing the number of component : "BIC" or "AIC"
`stop.crit` | stop criterion for EM algorithm
`display` | Boolean. Should the estimated parameters be displayed on the screen ?
`criterion` | "likelihood" or "parameter". The convergence of EM algo will be decided with regard to the increase of likelihood or lack of noticeable in parameter value.

### Details

### Value

### Note

### Author(s)

Paul Delmar and Julie Aubert

### References

### See Also

`compute.dif`,`compute.dif.paired`,`compute.BIC`

### Examples

[Package varmixt version 0.2-4 Index]