In the first of this series of posts on regression techniques we introduced the work-horse of predictive modeling, ordinary least squares regression (OLS), but concluded with the notion that while a common and useful technique, OLS has some notable weaknesses. In the last post we discussed its sensitivity to outliers and how to deal with that using… Read More »
We left off discussion in the last post on regression techniques with the statement that there are some known issues relating to Ordinary Least Squares (OLS) regression techniques. My goal in this series of posts is to introduce several variations on OLS that address one or more of these drawbacks. The first issue I will mention is related… Read More »
I just completed this semester’s series of lectures on regression methods in ISE/DSA 5103 Intelligent Data Analytics and I wanted to take a moment to call out a few key points. First, let me list the primary set of techniques that we covered along with links to the associated methods and package in R: Ordinary… Read More »