Robust linear discriminant analysis is performed by replacing the classical group means and withing group covariance matrix by robust equivalents based on MCD.
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.
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.
Class "LdaRobust"
, directly.
Class "Lda"
, by class "LdaRobust", distance 2.
No methods defined with class "Linda" in the signature.
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").
LdaRobust-class
, Lda-class
, LdaClassic
, LdaClassic-class