olsrr: Tools for Building OLS Regression Models

Tools designed to make it easier for users, particularly beginner/intermediate R users to build ordinary least squares regression models. Includes comprehensive regression output, heteroskedasticity tests, collinearity diagnostics, residual diagnostics, measures of influence, model fit assessment and variable selection procedures.

Version: 0.5.3
Depends: R (≥ 3.3)
Imports: car, data.table, ggplot2, goftest, graphics, gridExtra, nortest, Rcpp, stats, utils
LinkingTo: Rcpp
Suggests: covr, descriptr, knitr, rmarkdown, testthat, vdiffr, xplorerr
Published: 2020-02-10
Author: Aravind Hebbali [aut, cre]
Maintainer: Aravind Hebbali <hebbali.aravind at gmail.com>
BugReports: https://github.com/rsquaredacademy/olsrr/issues
License: MIT + file LICENSE
URL: https://olsrr.rsquaredacademy.com/, https://github.com/rsquaredacademy/olsrr
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: olsrr results

Downloads:

Reference manual: olsrr.pdf
Vignettes: Heteroscedasticity
Measures of Influence
Introduction to olsrr
Media
Collinearity Diagnostics, Model Fit & Variable Contribution
Residual Diagnostics
Variable Selection Methods
Package source: olsrr_0.5.3.tar.gz
Windows binaries: r-devel: olsrr_0.5.3.zip, r-devel-gcc8: olsrr_0.5.3.zip, r-release: olsrr_0.5.3.zip, r-oldrel: olsrr_0.5.3.zip
OS X binaries: r-release: olsrr_0.5.3.tgz, r-oldrel: olsrr_0.5.3.tgz
Old sources: olsrr archive

Reverse dependencies:

Reverse suggests: xplorerr

Linking:

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