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PCovR  

Principal Covariates Regression
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("PCovR", "2.7.2")



Attach the package and use:
library("PCovR")
Maintained by
Kristof Meers
[Scholar Profile | Author Map]
First Published: 2013-03-20
Latest Update: 2023-10-26
Description:
Analyzing regression data with many and/or highly collinear predictor variables, by simultaneously reducing the predictor variables to a limited number of components and regressing the criterion variables on these components (de Jong S. & Kiers H. A. L. (1992) ). Several rotation and model selection options are provided.
How to cite:
Kristof Meers (2013). PCovR: Principal Covariates Regression. R package version 2.7.2, https://cran.r-project.org/web/packages/PCovR. Accessed 10 Apr. 2025.
Previous versions and publish date:
1.0 (2013-03-20 13:15), 1.1 (2013-04-11 14:34), 2.0 (2013-12-09 17:07), 2.1 (2013-12-24 12:14), 2.2 (2014-01-22 13:08), 2.3 (2014-02-05 17:55), 2.4 (2014-02-28 16:02), 2.5 (2014-07-16 10:57), 2.6 (2015-05-05 16:14), 2.7.1 (2021-01-29 11:10), 2.7 (2017-06-19 15:57)
Other packages that cited PCovR R package
View PCovR citation profile
Other R packages that PCovR depends, imports, suggests or enhances
Complete documentation for PCovR
Functions, R codes and Examples using the PCovR R package
Some associated functions: ErrorRatio . PCovR-package . SortLoadings . alexithymia . pcovr . pcovr_est . promin . psychiatrists . tarrotob . wvarim . 
Some associated R codes: ErrorRatio.R . SortLoadings.R . pcovr.R . pcovr.default.R . pcovr_est.R . plot.pcovr.R . print.pcovr.R . promin.R . summary.pcovr.R . tarrotob.R . wvarim.R .  Full PCovR package functions and examples
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