PcaRobust-class {rrcov} | R Documentation |
The class PcaRobust
searves as a base class for deriving all other
classes representing the results of the robust Principal Component Analisys methods
A virtual Class: No objects may be created from it.
call
:"language"
center
:"vector"
the center of the data loadings
:"matrix"
the matrix
of variable loadings (i.e., a matrix whose columns contain the eigenvectors) eigenvalues
:"vector"
the eigenvalues scores
:"matrix"
the scores - the value
of the rotated data (the centred (and scaled if requested) data multiplied
by the rotation
matrix) is returned. Hence, cov(scores)
is the diagonal matrix diag(eigenvalues)
k
:"numeric"
number of (choosen) principal components sd
:"Uvector"
Score distances within the robust PCA subspace od
:"Uvector"
Orthogonal distances to the robust PCA subspace cutoff.sd
:"numeric"
Cutoff value for the score distancescutoff.od
:"numeric"
Cutoff values for the orthogonal distances flag
:"Uvector"
The observations whose score distance is larger
than cutoff.sd or whose orthogonal distance is larger than cutoff.od can be considered
as outliers and receive a flag equal to zero.
The regular observations receive a flag 1 n.obs
:"numeric"
the number of observations
Class "Pca"
, directly.
No methods defined with class "PcaRobust" in the signature.
Valentin Todorov valentin.todorov@chello.at
showClass("PcaRobust")