mda.start {mda}

Initialization for Mixture Discriminant Analysis

Description

Provide starting weights for the mda function which performs discriminant analysis by gaussian mixtures.

Usage

mda.start(x, g, subclasses = 3, trace.mda.start = FALSE,
          start.method = c("kmeans", "lvq"), tries = 5,
          criterion = c("misclassification", "deviance"), ...)

Arguments

x

The x data, or an mda object.

g

The response vector g.

subclasses

number of subclasses per class, as in mda.

trace.mda.start

Show results of each iteration.

start.method

Either "kmeans" or "lvq". The latter requires package class (from the VR package bundle.

tries

Number of random starts.

criterion

By default, classification errors on the training data. Posterior deviance is also an option.

...

arguments to be passed to the mda fitter when using posterior deviance.

Value

A list of weight matrices, one for each class.