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), that seeks to maximize the proportion of variance (in the response vector) being explained by a set of covariates.

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- Package
- pcev
- Title
- Principal Component of Explained Variance
- Version
- 2.2.2
- Description
- 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.
- Depends
- R (>= 3.0.0)
- Imports
- RMTstat, stats, corpcor
- License
- GPL (>= 2)
- LazyData
- true
- URL
- BugReports
- http://github.com/GreenwoodLab/pcev/issues
- Suggests
- knitr
- VignetteBuilder
- knitr
- RoxygenNote
- 6.0.1
- NeedsCompilation
- no
- Packaged
- 2018-02-03 23:05:56 UTC; mturgeon
- Author
- Maxime Turgeon [aut, cre], Aurelie Labbe [aut], Karim Oualkacha [aut], Stepan Grinek [aut]
- Maintainer
- Maxime Turgeon
- Repository
- CRAN
- Date/Publication
- 2018-02-03 23:14:47 UTC

`install.packages('pcev')`

2.2.2

a month ago

http://github.com/GreenwoodLab/pcev

Maxime Turgeon

GPL (>= 2)

R (>= 3.0.0)