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.
The (matched) function call.
Prior probabilities used, default to group proportions
number of observations in each class
the group means
the common covariance matrix
a matrix containing the linear discriminant functions
a vector containing the constants of each linear discriminant function
a character string giving the estimation method used
the training data set (same as the input parameter x of the constructor function)
grouping variable: a factor specifying the class for each observation.
wheather L1 median was used to compute group means.
"Lda", by class "LdaRobust", distance 2.
No methods defined with class "Linda" in the signature.
Valentin Todorov [email protected]
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/.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.