| PcaNA-class {rrcovNA} | R Documentation |
Class "PcaNA" Principal Components for incomplete data
Description
Contains the results of the computations of classical and robust principal components for incomplete data using an EM algorithm as descibed by Serneels and Verdonck (2008)
Objects from the Class
Objects can be created by calls of the form new("PcaNA", ...) but the
usual way of creating PcaNA objects is a call to the function
PcaNA which serves as a constructor.
Slots
call,center,scale,loadings,eigenvalues,scores,k,sd,od,cutoff.sd,cutoff.od,flag,n.obs:-
from the
"Pca"class. Ximp:the data matrix with imputed missing values
Extends
Class "Pca", directly.
Methods
- getQuan
signature(obj = "PcaNA"): ...
Author(s)
Valentin Todorov valentin.todorov@chello.at
References
Serneels S & Verdonck T (2008), Principal component analysis for data containing outliers and missing elements. Computational Statistics and Data Analisys, 52(3), 1712–1727 .
Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. Journal of Statistical Software, 32(3), 1–47. <doi:10.18637/jss.v032.i03>.
See Also
PcaRobust-class, Pca-class, PcaClassic, PcaClassic-class
Examples
showClass("PcaNA")