Nothing
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 highdimensional data when the number of features p dominates the number of samples n (p >> n paradigm), as generated, for instance, by highthroughput technologies.
Package details 


Author  Eric Bair [aut], JeanEudes Dazard [cre, ctb], Rob Tibshirani [ctb] 
Maintainer  JeanEudes Dazard <jeaneudes.dazard@case.edu> 
License  GPL (>= 3)  file LICENSE 
Version  1.12 
URL  http://wwwstat.stanford.edu/~tibs/superpc https://github.com/jedazard/superpc 
Package repository  View on CRAN 
Installation 
Install the latest version of this package by entering the following in R:

Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.