Estimating and Testing the Number of Interesting Components in Linear Dimension Reduction

For different linear dimension reduction methods like principal components analysis (PCA), independent components analysis (ICA) and supervised linear dimension reduction tests and estimates for the number of interesting components (ICs) are provided.


Reference manual

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0.3-4 by Klaus Nordhausen, 7 months ago

Browse source code at

Authors: Klaus Nordhausen [aut, cre] , Hannu Oja [aut] , David E. Tyler [aut] , Joni Virta [aut]

Documentation:   PDF Manual  

GPL (>= 2) license

Imports stats, graphics, Rcpp, ICSNP, survey, GGally, png, zoo, xts

Depends on JADE, ICS, ggplot2

Suggests knitr, rmarkdown, fICA

Linking to Rcpp, RcppArmadillo

Imported by KernelICA, tensorBSS.

Depended on by ssaBSS, tsBSS.

See at CRAN