QdaCov {rrcov} | R Documentation |
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, ...)
## Default S3 method:
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 |
Details
details
Value
Returns an S4 object of class QdaCov
Warning
Still an experimental version!
Author(s)
Valentin Todorov valentin.todorov@chello.at
References
Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. Journal of Statistical Software, 32(3), 1–47. doi:10.18637/jss.v032.i03.
See Also
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())
[Package rrcov version 1.7-5 Index]