This R package seeks to automate regression in the way that it is taught at the University of Wisconsin-River Falls in Math 327 - Applied Regression Analysis. I used this as a reference for how to create the package, and I used this as a reference for how to put it on GitHub. Here is the official manual for creating R packages.
DISCLAIMER: This package will not, and likely cannot, cover every possible scenario. It is, as such, not intended to replace the content of the class. Rather, it is intended as a supplemental method of answer validation.
If you don't have devtools installed, install it:
install.packages("devtools")
Load devtools and install the package in this repository:
library(devtools)
install_github("jack-thomas/uwrfRegression")
The following packages are included as part of this package. Please note that some of them are not yet completed.
carima(), AR(k) modeling.cmlr(), multiple linear regression.cslr(), simple linear regression.csts(), which does seasonal time series stuff.ctsr(), time series modeling using MAD.eSmooth(), exponential smoothing for time series.ts.poly(), polynomial time series regression.
Please feel free to shoot me an email: [email protected].