PcaCov-class | R Documentation |
Robust PCA are obtained by replacing the classical covariance matrix
by a robust covariance estimator. This can be one of the available
in rrcov
estimators, i.e. MCD, OGK, M, S or Stahel-Donoho estimator.
Objects can be created by calls of the form new("PcaCov", ...)
but the
usual way of creating PcaCov
objects is a call to the function
PcaCov
which serves as a constructor.
quan
:Object of class "numeric"
The quantile h
used throughout the algorithm
call
, center
, rank
, loadings
,
eigenvalues
, scores
, k
,
sd
, od
, cutoff.sd
, cutoff.od
,
flag
, n.obs
, eig0
, totvar0
:from the "Pca"
class.
Class "PcaRobust"
, directly.
Class "Pca"
, by class "PcaRobust", distance 2.
signature(obj = "PcaCov")
: ...
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. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.18637/jss.v032.i03")}.
PcaRobust-class
, Pca-class
, PcaClassic
, PcaClassic-class
showClass("PcaCov")
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