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


Reference manual: PCovR.pdf


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


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