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.
|Author||Eric Bair [aut], Jean-Eudes Dazard [cre, ctb], Rob Tibshirani [ctb]|
|Maintainer||Jean-Eudes Dazard <firstname.lastname@example.org>|
|License||GPL (>= 3) | file LICENSE|
|Package repository||View on CRAN|
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