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olr
View on CRAN: Click
here
Download and install olr package within the R console
Install from CRAN:
install.packages("olr")
Install from Github:
library("remotes")
install_github("cran/olr")
Install by package version:
library("remotes")
install_version("olr", "1.1")
Attach the package and use:
library("olr")
Maintained by
Mathew Fok
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-12-22
Latest Update: 2020-01-08
Description:
The optimal linear regression olr(), runs all the possible combinations of linear regression
equations. The olr() returns the equation which has the greatest adjusted R-squared term or the greatest R-squared term based
on the user's discretion. Essentially, the olr() returns the best fit equation out of all the possible equations. R-squared increases
with the addition of an explanatory variable whether it is 'significant' or not, thus this was developed to eliminate that conundrum.
Adjusted R-squared is preferred to overcome this phenomenon, but each combination will still produce different results and this will
return the best one. Complimentary functions are included which list all of the equations, all of the equations in ascending order,
a function to give the user a specific model's summary, and the list of adjusted R-squared terms & R-squared terms.
A 'Python' version is available at: .
How to cite:
Mathew Fok (2019). olr: Optimal Linear Regression. R package version 1.1, https://cran.r-project.org/web/packages/olr
Previous versions and publish date:
1.0 (2019-12-22 17:00)
Other packages that cited olr R package
View olr citation profile
Other R packages that olr depends,
imports, suggests or enhances
Functions, R codes and Examples using
the olr R package
Some associated functions: olr .
Some associated R codes: olr_function.R . Full olr package functions and examples
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