rrcov (version 1.7-2)

QdaCov: Robust Quadratic Discriminant Analysis

Description

Performs robust quadratic discriminant analysis and returns the results as an object of class QdaCov (aka constructor).

Usage

QdaCov(x, ...)
# S3 method for default
QdaCov(x, grouping, prior = proportions, tol = 1.0e-4,
                 method = CovControlMcd(), ...)

Value

Returns an S4 object of class QdaCov

Arguments

x

a matrix or data frame containing the explanatory variables (training set).

grouping

grouping variable: a factor specifying the class for each observation.

prior

prior probabilities, default to the class proportions for the training set.

tol

tolerance

method

method

...

arguments passed to or from other methods

Author

Valentin Todorov

Warning

Still an experimental version!

Details

details

References

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").

See Also

CovMcd

Examples

## Example anorexia
library(MASS)
data(anorexia)

## start with the classical estimates
qda <- QdaClassic(Treat~., data=anorexia)
predict(qda)@classification

## try now the robust LDA with the default method (MCD with pooled whitin cov matrix)
rqda <- QdaCov(Treat~., data= anorexia)
predict(rqda)@classification

## try the other methods
QdaCov(Treat~., data= anorexia, method="sde")
QdaCov(Treat~., data= anorexia, method="M")
QdaCov(Treat~., data= anorexia, method=CovControlOgk())