The class Qda serves as a base class for deriving
all other classes representing the results of classical
and robust Quadratic Discriminant Analisys methods
A virtual Class: No objects may be created from it.
call:the (matched) function call.
prior:prior probabilities used, default to group proportions
counts:number of observations in each class
center:the group means
cov:the group covariance matrices
covinv:the inverse of the group covariance matrices
covdet:the determinants of the group covariance matrices
method:a character string giving the estimation method used
X:the training data set (same as the input parameter x of the constructor function)
grp:grouping variable: a factor specifying the class for each observation.
control:object of class "CovControl" specifying which estimate
and with what estimation options to use for the group means and covariances
(or NULL for classical discriminant analysis)
signature(object = "Qda"): calculates prediction using the results in
object. An optional data frame or matrix in which to look for variables with which
to predict. If omitted, the scores are used. If the original fit used a formula or
a data frame or a matrix with column names, newdata must contain columns with the
same names. Otherwise it must contain the same number of columns,
to be used in the same order.
signature(object = "Qda"): prints the results
signature(object = "Qda"): prints summary information
Valentin Todorov valentin.todorov@chello.at
Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. Journal of Statistical Software, 32(3), 1--47. tools:::Rd_expr_doi("10.18637/jss.v032.i03").
QdaClassic, QdaClassic-class, QdaRobust-class