This package sprang from trying to avoid copying and pasting code repeatedly for my linear regression class. I wanted a more elegant way to check linear regression assumptions and run variable selction methods, so here it is. For now, all the code is in R/assumption_checking.R. There is documentation available for all the funtions via help(), but for your reference, here is a short description of each function in the package.
| Function | Description |
|---|---|
| cor_graphic | A nice graphic of the correlation matrix |
| jcreg_av | Square added variable plots |
| jcreg_boxplot | Beautified boxplot of residuals |
| jcreg_cooksd | Plot absolute value of cooks distance against observation number |
| jcreg_dfbetas | Matrix of DFBETAS plots against observation number |
| jcreg_dffits | Plot DFFITS against observation number |
| jcreg_hist | Histogram of residuals overlaid with normal curve |
| jcreg_qq | Quantile-Quantile plot of residuals |
| point_matrix | Square scatterplot matrix |
| resid_vs_fitted | Square residuals vs fitted values plot |
| resid_vs_pred | Matrix of residuals vs predictor plots |
| var_selection | Run multiple variable selection methods and compare the results |
The devtools package provides a convenient function for installing packages from github. You can use it as follows:
install.packages("devtools")
library(devtools)
install_github("https://github.com/mtnbikerjoshua/jcreg")I welcome suggestions, comments, and contributions. If you find a bug or want to request a feature please open an issue. If you simply want to make suggestions or comments or want to contact me directly, please send me an email at [email protected]. If you would like to contribute to the code or documentation, please fork the project and submit a pull request.