Package: superpc
Type: Package
Title: Supervised Principal Components
Version: 1.12
Date: 2020-10-19
Authors@R: c(person("Eric", "Bair",
                    role = "aut",
                    email = "ebair@email.unc.edu"),
             person("Jean-Eudes", "Dazard",
                    role = c("cre", "ctb"),
                    email = "jean-eudes.dazard@case.edu"),
             person("Rob", "Tibshirani",
                    role = "ctb",
	               email = "tibs@stanford.edu"))
Author: Eric Bair [aut], Jean-Eudes Dazard [cre, ctb], Rob Tibshirani
        [ctb]
Maintainer: Jean-Eudes Dazard <jean-eudes.dazard@case.edu>
Description: 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.
Depends: R (>= 3.5.0)
Imports: survival, stats, graphics, grDevices
NeedsCompilation: no
URL: http://www-stat.stanford.edu/~tibs/superpc,
        https://github.com/jedazard/superpc
License: GPL (>= 3) | file LICENSE
Archs: i386, x64
Repository: https://jedazard.r-universe.dev
Date/Publication: 2025-04-28 15:09:34 UTC
RemoteUrl: https://github.com/jedazard/superpc
RemoteRef: HEAD
RemoteSha: 45faf22b7eba84e75d55ae17f1e04d781928df95
Packaged: 2026-06-09 09:51:58 UTC; root