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), which seeks to maximize the proportion of variance (in the response vector) being explained by a set of covariates. It implements both the classic version and our extension of the algorithm on the case of high number of data points (p>>n).
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:
vignette("pcev")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.