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
Old sources: gspcr archive

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