pcev: Principal Component of Explained Variance

Principal component of explained variance (PCEV) is a statistical tool for the analysis of a multivariate response vector. It is a dimension-reduction technique, similar to Principal component analysis (PCA), which seeks the maximize the proportion of variance (in the response vector) being explained by a set of covariates.

Version: 1.1.1
Depends: R (≥ 3.0.0)
Imports: RMTstat, stats
Suggests: knitr
Published: 2016-12-05
Author: Maxime Turgeon [aut, cre], Aurelie Labbe [aut], Karim Oualkacha [aut]
Maintainer: Maxime Turgeon <maxime.turgeon at mail.mcgill.ca>
BugReports: http://github.com/GreenwoodLab/pcev/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: http://github.com/GreenwoodLab/pcev
NeedsCompilation: no
Materials: README NEWS
CRAN checks: pcev results

Downloads:

Reference manual: pcev.pdf
Vignettes: Principal Component of Explained Variance
Package source: pcev_1.1.1.tar.gz
Windows binaries: r-devel: pcev_1.1.1.zip, r-release: pcev_1.1.1.zip, r-oldrel: pcev_1.1.1.zip
OS X Mavericks binaries: r-release: pcev_1.1.1.tgz, r-oldrel: pcev_1.1.1.tgz

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