Class "Linda" - Robust method for LINear Discriminant Analysis

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Description

Robust linear discriminant analysis is performed by replacing the classical group means and withing group covariance matrix by robust equivalents based on MCD.

Objects from the Class

Objects can be created by calls of the form new("Linda", ...) but the usual way of creating Linda objects is a call to the function Linda which serves as a constructor.

Slots

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 common covariance matrix

ldf:

a matrix containing the linear discriminant functions

ldfconst:

a vector containing the constants of each linear discriminant function

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.

l1med:

wheather L1 median was used to compute group means.

Extends

Class "LdaRobust", directly. Class "Lda", by class "LdaRobust", distance 2.

Methods

No methods defined with class "Linda" in the signature.

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

See Also

LdaRobust-class, Lda-class, LdaClassic, LdaClassic-class

Examples

1
showClass("Linda")

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