## S3 method for class 'mda'
predict(object, newdata, type, prior, dimension, g, ...)
Arguments
object
a fitted mda object.
newdata
new data at which to make predictions. If missing, the
training data is used.
type
kind of predictions: type = "class" (default)
produces a fitted factor, type = "variates" produces a matrix
of discriminant variables (note that the maximal dimension is
determined by the number of subclasses), type = "posterior"
produces a matrix of posterior probabilities (based on a gaussian
assumption), type = "hierarchical" produces the predicted
class in sequence for models of dimensions specified by
dimension argument.
prior
the prior probability vector for each class; the
default is the training sample proportions.
dimension
the dimension of the space to be used, no larger
than the dimension component of object, and in general less
than the number of subclasses. dimension can be a vector for
use with type = "hierarchical".
g
???
...
further arguments to be passed to or from methods.
Value
An appropriate object depending on type. object has a
component fit which is regression fit produced by the
method argument to mda. There should be a
predict method for this object which is invoked. This method
should itself take as input object and optionally newdata.