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), that seeks to maximize the proportion of variance (in the response vector) being explained by a set of covariates.
| Version: | 2.2.2 |
| Depends: | R (≥ 3.0.0) |
| Imports: | RMTstat, stats, corpcor |
| Suggests: | knitr |
| Published: | 2018-02-03 |
| Author: | Maxime Turgeon [aut, cre], Aurelie Labbe [aut], Karim Oualkacha [aut], Stepan Grinek [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 |
| Citation: | pcev citation info |
| Materials: | README NEWS |
| CRAN checks: | pcev results |
| Reference manual: | pcev.pdf |
| Vignettes: |
Principal Component of Explained Variance |
| Package source: | pcev_2.2.2.tar.gz |
| Windows binaries: | r-devel: pcev_2.2.2.zip, r-release: pcev_2.2.2.zip, r-oldrel: pcev_2.2.2.zip |
| macOS binaries: | r-release (arm64): pcev_2.2.2.tgz, r-oldrel (arm64): pcev_2.2.2.tgz, r-release (x86_64): pcev_2.2.2.tgz, r-oldrel (x86_64): pcev_2.2.2.tgz |
| Old sources: | pcev archive |
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