R package which implements Principal components of explained variance (PCEV).
PCEV is a statistical tool for the analysis of a mutivariate response vector. It is a dimension-reduction technique, similar to Principal Components Analysis (PCA), that seeks to maximize the proportion of variance (in the response vector) being explained by a set of covariates. It implements three versions:
For the first two versions, we provide hypothesis testing based on Roy’s largest root.
For more information you can look at the vignette. Alternatively, if you have already installed the package along with the vignette, you can access the vignette from within
R by using the following command:
This package is available on CRAN. Alternatively, you can install from GitHub using the devtools package:
library(devtools) devtools::install_github('GreenwoodLab/pcev', build_vignettes = TRUE)
The main function is
computePCEV, and indeed most users will only need this one function. See the documentation for more information about its parameters and for some examples.