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.
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 |
DOI: | 10.32614/CRAN.package.gspcr |
Author: | Edoardo Costantini [aut, cre] |
Maintainer: | Edoardo Costantini <costantini.edoardo at yahoo.com> |
License: | MIT + file LICENSE |
NeedsCompilation: | no |
Materials: | README |
CRAN checks: | gspcr results |
Reference manual: | gspcr.pdf |
Vignettes: |
Vignette 1: Example analysis with GSPCR Vignette 2: GSPCR specification options Vignette 3: Alternatives approaches |
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 |
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.