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pcev  

Principal Component of Explained Variance
View on CRAN: Click here


Download and install pcev package within the R console
Install from CRAN:
install.packages("pcev")

Install from Github:
library("remotes")
install_github("cran/pcev")

Install by package version:
library("remotes")
install_version("pcev", "2.2.2")



Attach the package and use:
library("pcev")
Maintained by
Maxime Turgeon
[Scholar Profile | Author Map]
First Published: 2016-12-05
Latest Update: 2018-02-03
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.
How to cite:
Maxime Turgeon (2016). pcev: Principal Component of Explained Variance. R package version 2.2.2, https://cran.r-project.org/web/packages/pcev. Accessed 02 May. 2025.
Previous versions and publish date:
1.1.1 (2016-12-05 18:28), 2.2.1 (2017-10-11 05:30)
Other packages that cited pcev R package
View pcev citation profile
Other R packages that pcev depends, imports, suggests or enhances
Complete documentation for pcev
Functions, R codes and Examples using the pcev R package
Some associated functions: PcevObj . computePCEV . estimatePcev . methylation . pcev-package . permutePval . roysPval . wilksPval . 
Some associated R codes: estimatePcev.R . functions.R . methods.R . pcev.R .  Full pcev package functions and examples
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