bicEMtrain {mclust} | R Documentation

## Select models in discriminant analysis using BIC

### Description

For the ten available discriminant models the BIC is calulated. The models for one-dimensional data are "E" and "V"; for higher dimensions they are "EII", "VII", "EEI", "VEI", "EVI", "VVI", "EEE", "EEV", "VEV" and "VVV". This function is much faster than `cv1EMtrain`.

### Usage

    bicEMtrain(data, labels, modelNames)

### Arguments

`data` | A data matrix
`labels` | Labels for each row in the data matrix
`modelNames` | Vector of model names that should be tested.

### Value

Returns a vector where each element is the BIC for the corresponding model.

### Author(s)

C. Fraley

### See Also

`cv1EMtrain`

### Examples

    data(lansing)
    odd <- seq(from=1, to=nrow(lansing), by=2)
    round(bicEMtrain(lansing[odd,-3], labels=lansing[odd, 3]), 1)

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