mclust (version 2.1-14)

bicEMtrain: 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.

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)