PcaClassic-class {rrcov}R Documentation

Class "PcaClassic" - Principal Components Analysis

Description

Contains the results of a classical Principal Components Analysis

Objects from the Class

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

Slots

call:
Object of class "language"
center:
Object of class "vector" the center of the data
loadings:
Object of class "matrix" the matrix of variable loadings (i.e., a matrix whose columns contain the eigenvectors)
eigenvalues:
Object of class "vector" the eigenvalues
scores:
Object of class "matrix" the scores - the value of the projected on the space of the principal components data (the centred (and scaled if requested) data multiplied by the loadings matrix) is returned. Hence, cov(scores) is the diagonal matrix diag(eigenvalues)
k:
Object of class "numeric" number of (choosen) principal components
sd:
Object of class "Uvector" Score distances within the robust PCA subspace
od:
Object of class "Uvector" Orthogonal distances to the robust PCA subspace
cutoff.sd:
Object of class "numeric" Cutoff value for the score distances
cutoff.od:
Object of class "numeric" Cutoff values for the orthogonal distances
flag:
Object of class "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:
Object of class "numeric" the number of observations

Extends

Class "Pca", directly.

Methods

getQuan
signature(obj = "PcaClassic"): returns the number of observations used in the computation, i.e. n.obs

Author(s)

Valentin Todorov valentin.todorov@chello.at

See Also

PcaRobust-class, Pca-class, PcaClassic

Examples

showClass("PcaClassic")

[Package rrcov version 0.5-01 Index]