rrcov (version 1.5-2)

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(), ...)

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

Value

Returns an S4 object of class QdaCov

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. URL http://www.jstatsoft.org/v32/i03/.

See Also

CovMcd

Examples

# NOT RUN {
## 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())

# }