olsrr: Tools for Teaching and Learning OLS Regression

Tools for teaching and learning ordinary least squares regression. Includes comprehensive regression output, heteroskedasticity tests, collinearity diagnostics, residual diagnostics, measures of influence, model fit assessment and variable selection procedures.

Version: 0.1.0
Depends: R (≥ 3.2.4)
Imports: ggplot2, gridExtra, graphics, dplyr, magrittr, purrr, tibble, tidyr, nortest, goftest, Rcpp
LinkingTo: Rcpp
Suggests: testthat, covr, knitr, rmarkdown
Published: 2017-05-11
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://rsquaredacademy.github.io/olsrr/, https://github.com/rsquaredacademy/olsrr
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: olsrr results


Reference manual: olsrr.pdf
Vignettes: Heteroscedasticity
Measures of Influence
Introduction to olsrr
Collinearity Diagnostics, Model Fit & Variable Contribution
Residual Diagnostics
Variable Selection Methods
Package source: olsrr_0.1.0.tar.gz
Windows binaries: r-devel: olsrr_0.1.0.zip, r-release: olsrr_0.1.0.zip, r-oldrel: olsrr_0.1.0.zip
OS X El Capitan binaries: r-release: olsrr_0.1.0.tgz
OS X Mavericks binaries: r-oldrel: olsrr_0.1.0.tgz


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