The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

gspcr: Generalized Supervised Principal Component Regression

Generalization of supervised principal component regression (SPCR; Bair et al., 2006, <doi:10.1198/016214505000000628>) to support continuous, binary, and discrete variables as outcomes and predictors (inspired by the 'superpc' R package <https://cran.r-project.org/package=superpc>).

Version: 0.9.5
Depends: R (≥ 2.10)
Imports: dplyr, FactoMineR, ggplot2, MASS, MLmetrics, nnet, PCAmixdata, reshape2, rlang
Suggests: knitr, lmtest, patchwork, rmarkdown, superpc, testthat (≥ 3.0.0)
Published: 2024-04-12
Author: Edoardo Costantini ORCID iD [aut, cre]
Maintainer: Edoardo Costantini <costantini.edoardo at yahoo.com>
License: MIT + file LICENSE
NeedsCompilation: no
Materials: README
CRAN checks: gspcr results

Documentation:

Reference manual: gspcr.pdf
Vignettes: Vignette 1: Example analysis with GSPCR
Vignette 2: GSPCR specification options
Vignette 3: Alternatives approaches

Downloads:

Package source: gspcr_0.9.5.tar.gz
Windows binaries: r-devel: gspcr_0.9.5.zip, r-release: gspcr_0.9.5.zip, r-oldrel: gspcr_0.9.5.zip
macOS binaries: r-release (arm64): gspcr_0.9.5.tgz, r-oldrel (arm64): gspcr_0.9.5.tgz, r-release (x86_64): gspcr_0.9.5.tgz, r-oldrel (x86_64): gspcr_0.9.5.tgz
Old sources: gspcr archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=gspcr to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.