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PCovR: Principal Covariates Regression

Analyzing regression data with many and/or highly collinear predictor variables, by simultaneously reducing the predictor variables to a limited number of components and regressing the criterion variables on these components (de Jong S. & Kiers H. A. L. (1992) <doi:10.1016/0169-7439(92)80100-I>). Several rotation and model selection options are provided.

Version: 2.7.2
Depends: GPArotation, ThreeWay, MASS, stats, graphics, Matrix
Published: 2023-10-26
DOI: 10.32614/CRAN.package.PCovR
Author: Marlies Vervloet [aut, cre], Henk Kiers [aut], Eva Ceulemans [ctb]
Maintainer: Kristof Meers <kristof.meers+cran at kuleuven.be>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: PCovR results

Documentation:

Reference manual: PCovR.pdf

Downloads:

Package source: PCovR_2.7.2.tar.gz
Windows binaries: r-devel: PCovR_2.7.2.zip, r-release: PCovR_2.7.2.zip, r-oldrel: PCovR_2.7.2.zip
macOS binaries: r-release (arm64): PCovR_2.7.2.tgz, r-oldrel (arm64): PCovR_2.7.2.tgz, r-release (x86_64): PCovR_2.7.2.tgz, r-oldrel (x86_64): PCovR_2.7.2.tgz
Old sources: PCovR archive

Reverse dependencies:

Reverse imports: EFA.MRFA, vampyr

Linking:

Please use the canonical form https://CRAN.R-project.org/package=PCovR 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.