Skip to content
R notebooks that illustrate principles of variable selection in multiple regression
HTML
Branch: master
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
.gitattributes
.gitignore
LICENSE
README.md
challenges-of-multiple-regression.Rmd
challenges-of-multiple-regression.nb.html
multiple-regression-basics.Rmd
multiple-regression-basics.nb.html
principal-components-regression.Rmd
principal-components-regression.nb.html
reducing-the-number-of-covariates.Rmd
reducing-the-number-of-covariates.nb.html
what-is-multiple-regression-doing.Rmd
what-is-multiple-regression-doing.nb.html

README.md

An overview of variable selection in multiple regression

This repository contains a series of R notebooks I developed to illustrate some basic principles of variable selection in multiple regression. I make no claim to be an expert. I am simply sharing what I understand about the principles. You'll need to have RStudio installed to take full advantage of the R notebook features, but the open source version of RStudio has served my needs well,1 it will only cost you a little disk space.


  1. I've been using editors long enough, though, that I only use the editor in RStudio when I'm editing an R notebook. Otherwise, Emacs (https://www.gnu.org/software/emacs/emacs.html) is my editor of choice.

You can’t perform that action at this time.