Supervised Principal Components

Does prediction in the case of a censored survival outcome, or a regression outcome, using the "supervised principal component" approach. 'Superpc' is especially useful for high-dimensional data when the number of features p dominates the number of samples n (p >> n paradigm), as generated, for instance, by high-throughput technologies.


Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.


1.12 by Jean-Eudes Dazard, 7 months ago,

Browse source code at

Authors: Eric Bair [aut] , Jean-Eudes Dazard [cre, ctb] , Rob Tibshirani [ctb]

Documentation:   PDF Manual  

Task views: Survival Analysis

GPL (>= 3) | file LICENSE license

Imports survival, stats, graphics, grDevices

Suggested by caret, fscaret.

See at CRAN